PLB33540S0370-2693(18)30103-510.1016/j.physletb.2018.02.004The Author(s)Experiments

Fig. 1

Distributions for the signal (left) and for some dominant background processes (right) of the two observables chosen in the 0-jet (top), VBF (center), and boosted (bottom) categories in the μτh decay channel. The background processes are chosen for illustrative purpose for their separation from the signal. The Z→μμ background in the 0-jet category is concentrated in the regions where the visible mass is close to 90 GeV and is negligible when the τh candidate is reconstructed in the 3-prong decay mode. The Z→ττ background in the VBF category mostly lies at low mjj values whereas the distribution of VBF signal events extends to high mjj values. In the boosted category, the W+jets background, which behaves similarly to the QCD multijet background, is rather flat with respect to mττ, and is concentrated at low pTττ values. These distributions are not used as such to extract the results.

Fig. 1

Fig. 2

Control regions enriched in the W+jets background used in the maximum likelihood fit, together with the signal regions, to extract the results. The normalization of the predicted background distributions corresponds to the result of the global fit. These regions, defined with mT>80 GeV, control the yields of the W+jets background in the μτh and eτh channels. The constraints obtained in the boosted categories are propagated to the VBF categories of the corresponding channels.

Fig. 2

Fig. 3

Control regions enriched in the QCD multijet background used in the maximum likelihood fit, together with the signal regions, to extract the results. The normalization of the predicted background distributions corresponds to the result of the global fit. These regions, defined by selecting events with opposite-sign ℓ and τh candidates with ℓ passing inverted isolation conditions, control the yields of the QCD multijet background in the μτh and eτh channels. The constraints obtained in the boosted categories are propagated to the VBF categories of the corresponding channels.

Fig. 3

Fig. 4

Control regions enriched in the QCD multijet background used in the maximum likelihood fit, together with the signal regions, to extract the results. The normalization of the predicted background distributions corresponds to the result of the global fit. These regions, formed by selecting events with opposite-sign τh candidates passing relaxed isolation requirements, control the yields of the QCD multijet background in the τhτh channel.

Fig. 4

Fig. 5

Control region enriched in the tt‾ background, used in the maximum likelihood fit, together with the signal regions, to extract the results. The normalization of the predicted background distributions corresponds to the result of the global fit. This region, defined by inverting the pζ requirement and rejecting events with no jet in the eμ final state, is used to estimate the yields of the tt‾ background in all channels.

Fig. 5

Fig. 6

Observed and predicted 2D distributions in the VBF category of the τhτh decay channel. The normalization of the predicted background distributions corresponds to the result of the global fit. The signal distribution is normalized to its best fit signal strength. The background histograms are stacked. The “Others” background contribution includes events from diboson and single top quark production, as well as Higgs boson decays to a pair of W bosons. The background uncertainty band accounts for all sources of background uncertainty, systematic as well as statistical, after the global fit. The signal is shown both as a stacked filled histogram and an open overlaid histogram.

Fig. 6

Fig. 7

Observed and predicted 2D distributions in the VBF category of the μτh decay channel. The description of the histograms is the same as in Fig. 6.

Fig. 7

Fig. 8

Observed and predicted 2D distributions in the VBF category of the eτh decay channel. The description of the histograms is the same as in Fig. 6.

Fig. 8

Fig. 9

Observed and predicted 2D distributions in the VBF category of the eμ decay channel. The description of the histograms is the same as in Fig. 6.

Fig. 9

Fig. 10

Observed and predicted 2D distributions in the boosted category of the τhτh decay channel. The description of the histograms is the same as in Fig. 6.

Fig. 10

Fig. 11

Observed and predicted 2D distributions in the boosted category of the μτh decay channel. The description of the histograms is the same as in Fig. 6.

Fig. 11

Fig. 12

Observed and predicted 2D distributions in the boosted category of the eτh decay channel. The description of the histograms is the same as in Fig. 6.

Fig. 12

Fig. 13

Observed and predicted 2D distributions in the boosted category of the eμ decay channel. The description of the histograms is the same as in Fig. 6.

Fig. 13

Fig. 14

Observed and predicted distributions in the 0-jet category of the τhτh decay channel. The description of the histograms is the same as in Fig. 6.

Fig. 14

Fig. 15

Observed and predicted 2D distributions in the 0-jet category of the μτh decay channel. The description of the histograms is the same as in Fig. 6.

Fig. 15

Fig. 16

Observed and predicted 2D distributions in the 0-jet category of the eτh decay channel. The description of the histograms is the same as in Fig. 6.

Fig. 16

Fig. 17

Observed and predicted 2D distributions in the 0-jet category of the eμ decay channel. The description of the histograms is the same as in Fig. 6.

Fig. 17

Fig. 18

Distribution of the decimal logarithm of the ratio between the expected signal and the sum of expected signal and expected background in each bin of the mass distributions used to extract the results, in all signal regions. The background contributions are separated by decay channel. The inset shows the corresponding difference between the observed data and expected background distributions divided by the background expectation, as well as the signal expectation divided by the background expectation.

Fig. 18

Fig. 19

Combined observed and predicted mττ distributions. The top panel includes the VBF category of the μτh, eτh and eμ channels, and the bottom panel includes all other channels that make use of mττ instead of mvis for the signal strength fit. The binning reflects the one used in the 2D distributions, and does not allow merging of the two figures. The normalization of the predicted background distributions corresponds to the result of the global fit, while the signal is normalized to its best fit signal strength. The mass distributions for a constant range of the second dimension of the signal distributions are weighted according to S/(S+B), where S and B are computed, respectively, as the signal or background contribution in the mass distribution excluding the first and last bins. The “Others” background contribution includes events from diboson, tt‾, and single top quark production, as well as Higgs boson decay to a pair of W bosons and Z bosons decaying to a pair of light leptons. The background uncertainty band accounts for all sources of background uncertainty, systematic as well as statistical, after the global fit. The inset shows the corresponding difference between the observed data and expected background distributions, together with the signal expectation. The signal yield is not affected by the reweighting.

Fig. 19

Fig. 20

Local p-value and significance as a function of the SM Higgs boson mass hypothesis. The observation (red, solid) is compared to the expectation (blue, dashed) for a Higgs boson with a mass mH=125.09 GeV. The background includes Higgs boson decays to pairs of W bosons, with mH=125.09 GeV.

Fig. 20

Fig. 21

Best fit signal strength per category (top) and channel (bottom), for mH=125.09 GeV. The constraints from the global fit are used to extract each of the individual best fit signal strengths. The combined best fit signal strength is μ=1.09−0.26+0.27.

Fig. 21

Fig. 22

Scan of the negative log-likelihood difference as a function of κV and κf, for mH=125.09 GeV. All nuisance parameters are profiled for each point. For this scan, the pp→H→WW contribution is treated as a signal process.

Fig. 22

Table 1

Kinematic selection requirements for the four di-τ decay channels. The trigger requirement is defined by a combination of trigger candidates with pT over a given threshold (in GeV), indicated inside parentheses. The pseudorapidity thresholds come from trigger and object reconstruction constraints. The pT thresholds for the lepton selection are driven by the trigger requirements, except for the leading τh candidate in the τhτh channel, the τh candidate in the μτh and eτh channels, and the muon in the eμ channel, where they have been optimized to increase the significance of the analysis.

Table 1

ChannelTrigger requirementLepton selectionpT (GeV)ηIsolationτhτhτh(35)&τh(35)pTτh>50&40|ητh|<2.1MVA τh IDμτhμ(22)pTμ>23|ημ|<2.1Iμ<0.15pTτh>30|ητh|<2.3MVA τh IDμ(19)&τh(21)20<pTμ<23|ημ|<2.1Iμ<0.15pTτh>30|ητh|<2.3MVA τh IDeτhe(25)pTe>26|ηe|<2.1Ie<0.1pTτh>30|ητh|<2.3MVA τh IDeμe(12)&μ(23)pTe>13|ηe|<2.5Ie<0.15pTμ>24|ημ|<2.4Iμ<0.2e(23)&μ(8)pTe>24|ηe|<2.5Ie<0.15pTμ>15|ημ|<2.4Iμ<0.2Table 2

Category selection and observables used to build the 2D kinematic distributions. The events neither selected in the 0-jet nor in the VBF category are included in the boosted category, as denoted by “Others”.

Table 2

0-jetVBFBoostedSelectionτhτhNo jet≥2 jets, pTττ>100GeV, Δηjj>2.5OthersμτhNo jet≥2 jets, mjj>300 GeV, pTττ>50GeV, pTτh>40GeVOtherseτhNo jet≥2 jets, mjj>300 GeV, pTττ>50GeVOtherseμNo jet2 jets, mjj>300 GeVOthersObservablesτhτhmττmjj, mττpTττ, mττμτhτh decay mode, mvismjj, mττpTττ, mττeτhτh decay mode, mvismjj, mττpTττ, mττeμpTμ, mvismjj, mττpTττ, mττTable 3

Sources of systematic uncertainty. If the global fit to the signal and control regions, described in the next section, significantly constrains these uncertainties, the values of the uncertainties after the global fit are indicated in the third column. The acronyms CR and ID stand for control region and identification, respectively.

Table 3

Source of uncertaintyPrefitPostfit (%)τh energy scale1.2% in energy scale0.2–0.3e energy scale1–2.5% in energy scale0.2–0.5e misidentified as τh energy scale3% in energy scale0.6–0.8μ misidentified as τh energy scale1.5% in energy scale0.3–1.0Jet energy scaleDependent upon pT and η–p→Tmiss energy scaleDependent upon pT and η–τh ID & isolation5% per τh3.5τh trigger5% per τh3τh reconstruction per decay mode3% migration between decay modes2e ID & isolation & trigger2%–μ ID & isolation & trigger2%–e misidentified as τh rate12%5μ misidentified as τh rate25%3–8Jet misidentified as τh rate20% per 100 GeV τh pT15Z→ττ/ℓℓ estimationNormalization: 7–15%3–15Uncertainty in mℓℓ/ττ, pT(ℓℓ/ττ),–and mjj correctionsW+jets estimationNormalization (eμ, τhτh): 4–20%–Unc. from CR (eτh, μτh): ≃5–15–Extrap. from high-mT CR (eτh, μτh): 5–10%–QCD multijet estimationNormalization (eμ): 10–20%5–20%Unc. from CR (eτh, τhτh, μτh): ≃5–15%–Extrap. from anti-iso. CR (eτh, μτh): 20%7–10Extrap. from anti-iso. CR (τhτh): 3–15%3–10Diboson normalization5%–Single top quark normalization5%–tt‾ estimationNormalization from CR: ≃5%–Uncertainty on top quark pT reweighting–Integrated luminosity2.5%–b-tagged jet rejection (eμ)3.5–5.0%–Limited number of eventsStatistical uncertainty in individual bins–Signal theoretical uncertaintyUp to 20%–Table 4

Background and signal expectations, together with the number of observed events, for bins in the signal region for which log10⁡(S/(S+B))>−0.9, where S and B are, respectively, the number of expected signal events for a Higgs boson with a mass mH=125.09 GeV and of expected background events, in those bins. The background uncertainty accounts for all sources of background uncertainty, systematic as well as statistical, after the global fit. The contribution from “other backgrounds” includes events from diboson and single top quark production. The contribution from Higgs boson decays to a pair of W bosons is zero in these bins.

Table 4

ProcesseμeτhμτhτhτhZ→ττ5.8 ± 2.221.2 ± 3.334.6 ± 4.989.1 ± 6.9Z→ee/μμ0.0 ± 0.02.9 ± 0.23.7 ± 0.25.0 ± 0.2tt‾+jets1.9 ± 0.110.4 ± 0.322.2 ± 1.813.9 ± 0.5W+jets0.8 ± 0.024.0 ± 0.36.6 ± 1.37.6 ± 0.8QCD multijet2.1 ± 0.33.3 ± 2.55.0 ± 1.335.5 ± 2.1Other backgrounds1.4 ± 0.15.2 ± 0.26.1 ± 0.27.3 ± 0.2ggH,H→ττ0.6 ± 0.15.0 ± 0.66.0 ± 0.627.4 ± 2.1VBF H→ττ2.8 ± 0.35.1 ± 0.512.55 ± 1.017.5 ± 1.0VH,H→ττ0.0 ± 0.00.3 ± 0.00.2 ± 0.01.3 ± 0.1Total backgrounds12.1 ± 2.246.5 ± 4.177.7 ± 5.5156.2 ± 7.3Total signal3.4 ± 0.410.9 ± 0.819.2 ± 1.448.3 ± 2.6Observed115491207Observation of the Higgs boson decay to a pair of τ leptons with the CMS detector

The CMS Collaboration

⋆

A.M.

Sirunyan

TumasyanYerevan Physics Institute, Yerevan, ArmeniaYerevan Physics InstituteYerevanArmenia

Adam

Ambrogi

Asilar

Bergauer

Brandstetter

Brondolin

Dragicevic

Erö

Flechl

Friedl

Frühwirth

V.M.

Ghete

Grossmann

Hrubec

Jeitler

König

Krammer

Krätschmer

Liko

Madlener

Mikulec

Pree

Rabady

Rad

Rohringer

Schieck

Schöfbeck

Spanring

Spitzbart

Waltenberger

Wittmann

C.-E.

Wulz

ZaruckiInstitut für Hochenergiephysik, Wien, AustriaInstitut für HochenergiephysikWienAustria1

Also at Vienna University of Technology, Vienna, Austria.

Chekhovsky

Mossolov

Suarez GonzalezInstitute for Nuclear Problems, Minsk, BelarusInstitute for Nuclear ProblemsMinskBelarus

E.A.

De Wolf

Di Croce

Janssen

Lauwers

Van Haevermaet

Van Mechelen

Van RemortelUniversiteit Antwerpen, Antwerpen, BelgiumUniversiteit AntwerpenAntwerpenBelgium

Abu Zeid

Blekman

D'Hondt

De Bruyn

De Clercq

Deroover

Flouris

Lontkovskyi

Lowette

Moortgat

Moreels

Python

Skovpen

Tavernier

Van Doninck

Van Mulders

Van ParijsVrije Universiteit Brussel, Brussel, BelgiumVrije Universiteit BrusselBrusselBelgium

Beghin

Brun

Clerbaux

De Lentdecker

Delannoy

Fasanella

Favart

Goldouzian

Grebenyuk

Karapostoli

Lenzi

Luetic

Maerschalk

Marinov

Randle-conde

Seva

Vander Velde

Vanlaer

Vannerom

Yonamine

Zenoni

Zhang

Université Libre de Bruxelles, Bruxelles, BelgiumUniversité Libre de BruxellesBruxellesBelgium2

Also at State Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, China.

Cimmino

Cornelis

Dobur

Fagot

Gul

Khvastunov

Poyraz

Roskas

Salva

Tytgat

Verbeke

ZaganidisGhent University, Ghent, BelgiumGhent UniversityGhentBelgium

Bakhshiansohi

Bondu

Brochet

Bruno

Caputo

Caudron

De Visscher

Delaere

Delcourt

Francois

Giammanco

Jafari

Komm

Krintiras

Lemaitre

Magitteri

Mertens

Musich

Piotrzkowski

Quertenmont

Vidal Marono

WertzUniversité Catholique de Louvain, Louvain-la-Neuve, BelgiumUniversité Catholique de LouvainLouvain-la-NeuveBelgium

BeliyUniversité de Mons, Mons, BelgiumUniversité de MonsMonsBelgium

W.L.

Aldá Júnior

F.L.

Alves

G.A.

Alves

Brito

Correa Martins Junior

Hensel

Moraes

M.E.

Pol

Rebello TelesCentro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, BrazilCentro Brasileiro de Pesquisas FisicasRio de JaneiroBrazil

Belchior Batista Das Chagas

Carvalho

Chinellato

Coelho

Custódio

E.M.

Da Costa

G.G.

Da Silveira

De Jesus Damiao

Fonseca De Souza

L.M.

Huertas Guativa

Malbouisson

Melo De Almeida

Mora Herrera

Mundim

Nogima

Santoro

Sznajder

E.J.

Tonelli Manganote

Torres Da Silva De Araujo

Vilela PereiraUniversidade do Estado do Rio de Janeiro, Rio de Janeiro, BrazilUniversidade do Estado do Rio de JaneiroRio de JaneiroBrazil3

Also at Universidade Estadual de Campinas, Campinas, Brazil.

Also at Universidade Federal de Pelotas, Pelotas, Brazil.

Ahuja

C.A.

Bernardes

T.R.

Fernandez Perez Tomei

E.M.

Gregores

P.G.

Mercadante

S.F.

Novaes

Sandra S.

Padula

Romero Abad

J.C.

Ruiz Vargas

aUniversidade Estadual Paulista, São Paulo, BrazilUniversidade Estadual PaulistaSão PauloBrazilbUniversidade Federal do ABC, São Paulo, BrazilUniversidade Federal do ABCSão PauloBrazil

Aleksandrov

Hadjiiska

Iaydjiev

Misheva

Rodozov

Shopova

Stoykova

SultanovInstitute for Nuclear Research and Nuclear Energy of Bulgaria Academy of Sciences, BulgariaInstitute for Nuclear Research and Nuclear Energy of Bulgaria Academy of SciencesBulgaria

Dimitrov

Glushkov

Litov

Pavlov

PetkovUniversity of Sofia, Sofia, BulgariaUniversity of SofiaSofiaBulgaria

Fang

Gao

Beihang University, Beijing, ChinaBeihang UniversityBeijingChina5

Also at Université Libre de Bruxelles, Bruxelles, Belgium.

Ahmad

J.G.

Bian

G.M.

Chen

H.S.

Chen

C.H.

Jiang

Leggat

Liao

Liu

Romeo

S.M.

Shaheen

Spiezia

Tao

Wang

Yazgan

Zhang

ZhaoInstitute of High Energy Physics, Beijing, ChinaInstitute of High Energy PhysicsBeijingChina

Ban

Chen

Liu

Mao

S.J.

Qian

Wang

XuState Key Laboratory of Nuclear Physics and Technology, Peking University, Beijing, ChinaState Key Laboratory of Nuclear Physics and TechnologyPeking UniversityBeijingChina

Avila

Cabrera

L.F.

Chaparro Sierra

Florez

C.F.

González Hernández

J.D.

Ruiz AlvarezUniversidad de Los Andes, Bogota, ColombiaUniversidad de Los AndesBogotaColombia

Courbon

Godinovic

Lelas

Puljak

P.M.

Ribeiro Cipriano

SculacUniversity of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, Split, CroatiaUniversity of SplitFaculty of Electrical Engineering, Mechanical Engineering and Naval ArchitectureSplitCroatia

Antunovic

KovacUniversity of Split, Faculty of Science, Split, CroatiaUniversity of SplitFaculty of ScienceSplitCroatia

Brigljevic

Ferencek

Kadija

Mesic

Starodumov

SusaInstitute Rudjer Boskovic, Zagreb, CroatiaInstitute Rudjer BoskovicZagrebCroatia6

Also at Institute for Theoretical and Experimental Physics, Moscow, Russia.

M.W.

Ather

Attikis

Mavromanolakis

Mousa

Nicolaou

Ptochos

P.A.

Razis

RykaczewskiUniversity of Cyprus, Nicosia, CyprusUniversity of CyprusNicosiaCyprus

Finger

FingerJr.

Charles University, Prague, Czech RepublicCharles UniversityPragueCzech Republic7

Also at Joint Institute for Nuclear Research, Dubna, Russia.

Carrera JarrinUniversidad San Francisco de Quito, Quito, EcuadorUniversidad San Francisco de QuitoQuitoEcuador

Assran

Elgammal

Mahrous

Academy of Scientific Research and Technology of the Arab Republic of Egypt, Egyptian Network of High Energy Physics, Cairo, EgyptAcademy of Scientific Research and Technology of the Arab Republic of EgyptEgyptian Network of High Energy PhysicsCairoEgypt8

Also at Suez University, Suez, Egypt.

Now at British University in Egypt, Cairo, Egypt.

Now at Helwan University, Cairo, Egypt.

R.K.

Dewanjee

Kadastik

Perrini

Raidal

Tiko

VeelkenNational Institute of Chemical Physics and Biophysics, Tallinn, EstoniaNational Institute of Chemical Physics and BiophysicsTallinnEstonia

Eerola

Pekkanen

VoutilainenDepartment of Physics, University of Helsinki, Helsinki, FinlandDepartment of PhysicsUniversity of HelsinkiHelsinkiFinland

Härkönen

Järvinen

Karimäki

Kinnunen

Lampén

Lassila-Perini

Lehti

Lindén

Luukka

Tuominen

Tuominiemi

TuovinenHelsinki Institute of Physics, Helsinki, FinlandHelsinki Institute of PhysicsHelsinkiFinland

Talvitie

TuuvaLappeenranta University of Technology, Lappeenranta, FinlandLappeenranta University of TechnologyLappeenrantaFinland

Besancon

Couderc

Dejardin

Denegri

J.L.

Faure

Ferri

Ganjour

Ghosh

Givernaud

Gras

Hamel de Monchenault

Jarry

Kucher

Locci

Machet

Malcles

Negro

Rander

Rosowsky

M.Ö.

Sahin

TitovIRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, FranceIRFUCEAUniversité Paris-SaclayGif-sur-YvetteFrance

Abdulsalam

Amendola

Antropov

Baffioni

Beaudette

Busson

Cadamuro

Charlot

Granier de Cassagnac

Lisniak

Lobanov

Martin Blanco

Nguyen

Ochando

Ortona

Paganini

Pigard

Salerno

J.B.

Sauvan

Sirois

A.G.

Stahl Leiton

Strebler

Yilmaz

Zabi

ZghicheLaboratoire Leprince-Ringuet, Ecole polytechnique, CNRS/IN2P3, Université Paris-Saclay, Palaiseau, FranceLaboratoire Leprince-RinguetEcole polytechniqueCNRS/IN2P3Université Paris-SaclayPalaiseauFrance

J.-L.

Agram

Andrea

Bloch

J.-M.

Brom

Buttignol

E.C.

Chabert

Chanon

Collard

Conte

Coubez

J.-C.

Fontaine

Gelé

Goerlach

Jansová

A.-C.

Le Bihan

Tonon

Van HoveUniversité de Strasbourg, CNRS, IPHC UMR 7178, F-67000 Strasbourg, FranceUniversité de StrasbourgCNRSIPHC UMR 7178Strasbourg

F-67000

France11

Also at Université de Haute Alsace, Mulhouse, France.

GadratCentre de Calcul de l'Institut National de Physique Nucleaire et de Physique des Particules, CNRS/IN2P3, Villeurbanne, FranceCentre de Calcul de l'Institut National de Physique Nucleaire et de Physique des ParticulesCNRS/IN2P3VilleurbanneFrance

Beauceron

Bernet

Boudoul

Chierici

Contardo

Depasse

El Mamouni

Fay

Finco

Gascon

Gouzevitch

Grenier

Ille

Lagarde

I.B.

Laktineh

Lethuillier

Mirabito

A.L.

Pequegnot

Perries

Popov

Sordini

Vander Donckt

ViretUniversité de Lyon, Université Claude Bernard Lyon 1, CNRS-IN2P3, Institut de Physique Nucléaire de Lyon, Villeurbanne, FranceUniversité de LyonUniversité Claude Bernard Lyon 1CNRS-IN2P3Institut de Physique Nucléaire de LyonVilleurbanneFrance12

Also at Skobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, Russia.

Khvedelidze

Georgian Technical University, Tbilisi, GeorgiaGeorgian Technical UniversityTbilisiGeorgia

Tsamalaidze

Tbilisi State University, Tbilisi, GeorgiaTbilisi State UniversityTbilisiGeorgia

Autermann

Feld

M.K.

Kiesel

Klein

Lipinski

Preuten

Schomakers

Schulz

Verlage

Zhukov

RWTH Aachen University, I. Physikalisches Institut, Aachen, GermanyRWTH Aachen UniversityI. Physikalisches InstitutAachenGermany

Albert

Dietz-Laursonn

Duchardt

Endres

Erdmann

Erdweg

Esch

Fischer

Güth

Hamer

Hebbeker

Heidemann

Hoepfner

Knutzen

Merschmeyer

Meyer

Millet

Mukherjee

Pook

Radziej

Reithler

Rieger

Scheuch

Teyssier

ThüerRWTH Aachen University, III. Physikalisches Institut A, Aachen, GermanyRWTH Aachen UniversityIII. Physikalisches Institut AAachenGermany

Flügge

Kargoll

Kress

Künsken

Lingemann

Müller

Nehrkorn

Nowack

Pistone

Pooth

Stahl

RWTH Aachen University, III. Physikalisches Institut B, Aachen, GermanyRWTH Aachen UniversityIII. Physikalisches Institut BAachenGermany13

Also at CERN, European Organization for Nuclear Research, Geneva, Switzerland.

Aldaya Martin

Arndt

Asawatangtrakuldee

Beernaert

Behnke

Behrens

Bermúdez Martínez

A.A.

Bin Anuar

Borras

Botta

Campbell

Connor

Contreras-Campana

Costanza

Diez Pardos

Eckerlin

Eckstein

Eichhorn

Eren

Gallo

Garay Garcia

Geiser

Gizhko

J.M.

Grados Luyando

Grohsjean

Gunnellini

Guthoff

Harb

Hauk

Hempel

Jung

Kalogeropoulos

Kasemann

Keaveney

Kleinwort

Korol

Krücker

Lange

Lelek

Lenz

Leonard

Lipka

Lohmann

Mankel

I.-A.

Melzer-Pellmann

A.B.

Meyer

Mittag

Mnich

Mussgiller

Ntomari

Pitzl

Raspereza

Roland

Savitskyi

Saxena

Shevchenko

Spannagel

Stefaniuk

G.P.

Van Onsem

Walsh

Wen

Wichmann

Wissing

ZenaievDeutsches Elektronen-Synchrotron, Hamburg, GermanyDeutsches Elektronen-SynchrotronHamburgGermany14

Also at RWTH Aachen University, III. Physikalisches Institut A, Aachen, Germany.

Also at University of Hamburg, Hamburg, Germany.

Also at Brandenburg University of Technology, Cottbus, Germany.

Bein

Blobel

Centis Vignali

Dreyer

Garutti

Gonzalez

Haller

Hinzmann

Hoffmann

Karavdina

Klanner

Kogler

Kovalchuk

Kurz

Lapsien

Marchesini

Marconi

Meyer

Niedziela

Nowatschin

Pantaleo

Peiffer

Perieanu

Scharf

Schleper

Schmidt

Schumann

Schwandt

Sonneveld

Stadie

Steinbrück

F.M.

Stober

Stöver

Tholen

Troendle

Usai

Vanelderen

Vanhoefer

VormwaldUniversity of Hamburg, Hamburg, GermanyUniversity of HamburgHamburgGermany

Akbiyik

Barth

Baur

Butz

Caspart

Chwalek

Colombo

De Boer

Dierlamm

Freund

Friese

Giffels

Haitz

Hartmann

S.M.

Heindl

Husemann

Kassel

Kudella

Mildner

M.U.

Mozer

Th.

Müller

Plagge

Quast

Rabbertz

Schröder

Shvetsov

Sieber

H.J.

Simonis

Ulrich

Wayand

Weber

Weiler

Williamson

Wöhrmann

WolfInstitut für Experimentelle Kernphysik, Karlsruhe, GermanyInstitut für Experimentelle KernphysikKarlsruheGermany

Anagnostou

Daskalakis

Geralis

V.A.

Giakoumopoulou

Kyriakis

Loukas

Topsis-GiotisInstitute of Nuclear and Particle Physics (INPP), NCSR Demokritos, Aghia Paraskevi, GreeceInstitute of Nuclear and Particle Physics (INPP)NCSR DemokritosAghia ParaskeviGreece

Karathanasis

Kesisoglou

Panagiotou

SaoulidouNational and Kapodistrian University of Athens, Athens, GreeceNational and Kapodistrian University of AthensAthensGreece

KousourisNational Technical University of Athens, Athens, GreeceNational Technical University of AthensAthensGreece

Evangelou

Foudas

Kokkas

Mallios

Manthos

Papadopoulos

Paradas

Strologas

F.A.

TriantisUniversity of Ioánnina, Ioánnina, GreeceUniversity of IoánninaIoánninaGreece

Csanad

Filipovic

Pasztor

G.I.

Veres

MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd University, Budapest, HungaryMTA-ELTE Lendület CMS Particle and Nuclear Physics GroupEötvös Loránd UniversityBudapestHungary17

Also at MTA-ELTE Lendület CMS Particle and Nuclear Physics Group, Eötvös Loránd University, Budapest, Hungary.

Bencze

Hajdu

Horvath

Á.

Hunyadi

Sikler

Veszpremi

A.J.

ZsigmondWigner Research Centre for Physics, Budapest, HungaryWigner Research Centre for PhysicsBudapestHungary18

Also at Institute of Nuclear Research ATOMKI, Debrecen, Hungary.

Beni

Czellar

Karancsi

Makovec

Molnar

SzillasiInstitute of Nuclear Research ATOMKI, Debrecen, HungaryInstitute of Nuclear Research ATOMKIDebrecenHungary19

Also at Institute of Physics, University of Debrecen, Debrecen, Hungary.

Bartók

Raics

Z.L.

Trocsanyi

UjvariInstitute of Physics, University of Debrecen, Debrecen, HungaryInstitute of PhysicsUniversity of DebrecenDebrecenHungary

Choudhury

J.R.

KomaragiriIndian Institute of Science (IISc), Bangalore, IndiaIndian Institute of Science (IISc)BangaloreIndia

Bahinipati

Bhowmik

Mal

Mandal

Nayak

D.K.

Sahoo

S.K.

SwainNational Institute of Science Education and Research, Bhubaneswar, IndiaNational Institute of Science Education and ResearchBhubaneswarIndia20

Also at Indian Institute of Technology Bhubaneswar, Bhubaneswar, India.

Also at Institute of Physics, Bhubaneswar, India.

Bansal

S.B.

Beri

Bhatnagar

Chawla

Dhingra

A.K.

Kalsi

Kaur

Kumar

Kumari

Mehta

J.B.

Singh

WaliaPanjab University, Chandigarh, IndiaPanjab UniversityChandigarhIndia

Ashok

Kumar

Aashaq

Shah

Bhardwaj

Chauhan

B.C.

Choudhary

R.B.

Garg

Keshri

Kumar

Malhotra

Naimuddin

Ranjan

SharmaUniversity of Delhi, Delhi, IndiaUniversity of DelhiDelhiIndia

Bhardwaj

Bhattacharya

Bhawandeep

Dey

Dutt

Dutta

Ghosh

Majumdar

Modak

Mondal

Mukhopadhyay

Nandan

Purohit

Roy

Roy Chowdhury

Sarkar

Sharan

ThakurSaha Institute of Nuclear Physics, HBNI, Kolkata, IndiaSaha Institute of Nuclear PhysicsHBNIKolkataIndia

P.K.

BeheraIndian Institute of Technology Madras, Madras, IndiaIndian Institute of Technology MadrasMadrasIndia

Chudasama

Dutta

Jha

Kumar

A.K.

Mohanty

P.K.

Netrakanti

L.M.

Pant

Shukla

TopkarBhabha Atomic Research Centre, Mumbai, IndiaBhabha Atomic Research CentreMumbaiIndia

Aziz

Dugad

Mahakud

Mitra

G.B.

Mohanty

Sur

SutarTata Institute of Fundamental Research-A, Mumbai, IndiaTata Institute of Fundamental Research-AMumbaiIndia

Banerjee

Bhattacharya

Chatterjee

Das

Guchait

Sa.

Jain

Kumar

Maity

Majumder

Mazumdar

Sarkar

Wickramage

Tata Institute of Fundamental Research-B, Mumbai, IndiaTata Institute of Fundamental Research-BMumbaiIndia22

Also at University of Visva-Bharati, Santiniketan, India.

Also at University of Ruhuna, Matara, Sri Lanka.

Chauhan

Dube

Hegde

Kapoor

Kothekar

Pandey

Rane

SharmaIndian Institute of Science Education and Research (IISER), Pune, IndiaIndian Institute of Science Education and Research (IISER)PuneIndia

Chenarani

Eskandari Tadavani

S.M.

Etesami

Khakzad

Mohammadi Najafabadi

Naseri

Paktinat Mehdiabadi

Rezaei Hosseinabadi

Safarzadeh

ZeinaliInstitute for Research in Fundamental Sciences (IPM), Tehran, IranInstitute for Research in Fundamental Sciences (IPM)TehranIran24

Also at Isfahan University of Technology, Isfahan, Iran.

Also at Yazd University, Yazd, Iran.

Also at Plasma Physics Research Center, Science and Research Branch, Islamic Azad University, Tehran, Iran.

Felcini

GrunewaldUniversity College Dublin, Dublin, IrelandUniversity College DublinDublinIreland

Abbrescia

Calabria

Colaleo

Creanza

Cristella

De Filippis

De Palma

Errico

Fiore

Iaselli

Lezki

Maggi

Miniello

Nuzzo

Pompili

Pugliese

Radogna

Ranieri

Selvaggi

Sharma

Silvestris

Venditti

Verwilligen

aINFN Sezione di Bari, Bari, ItalyINFN Sezione di BariBariItalybUniversità di Bari, Bari, ItalyUniversità di BariBariItalycPolitecnico di Bari, Bari, ItalyPolitecnico di BariBariItaly

Abbiendi

Battilana

Bonacorsi

Braibant-Giacomelli

Campanini

Capiluppi

Castro

F.R.

Cavallo

S.S.

Chhibra

Codispoti

Cuffiani

G.M.

Dallavalle

Fabbri

Fanfani

Fasanella

Giacomelli

Grandi

Guiducci

Marcellini

Masetti

Montanari

F.L.

Navarria

Perrotta

A.M.

Rossi

Rovelli

G.P.

Siroli

Tosi

aINFN Sezione di Bologna, Bologna, ItalyINFN Sezione di BolognaBolognaItalybUniversità di Bologna, Bologna, ItalyUniversità di BolognaBolognaItaly

Albergo

Costa

Di Mattia

Giordano

Potenza

Tricomi

Tuve

aINFN Sezione di Catania, Catania, ItalyINFN Sezione di CataniaCataniaItalybUniversità di Catania, Catania, ItalyUniversità di CataniaCataniaItaly

Barbagli

Chatterjee

Ciulli

Civinini

D'Alessandro

Focardi

Lenzi

Meschini

Paoletti

Russo

Sguazzoni

Strom

Viliani

aINFN Sezione di Firenze, Firenze, ItalyINFN Sezione di FirenzeFirenzeItalybUniversità di Firenze, Firenze, ItalyUniversità di FirenzeFirenzeItaly27

Also at Università degli Studi di Siena, Siena, Italy.

Benussi

Bianco

Fabbri

Piccolo

Primavera

INFN Laboratori Nazionali di Frascati, Frascati, ItalyINFN Laboratori Nazionali di FrascatiFrascatiItaly

Calvelli

Ferro

Robutti

Tosi

aINFN Sezione di Genova, Genova, ItalyINFN Sezione di GenovaGenovaItalybUniversità di Genova, Genova, ItalyUniversità di GenovaGenovaItaly

Benaglia

Brianza

Brivio

Ciriolo

M.E.

Dinardo

Fiorendi

Gennai

Ghezzi

Govoni

Malberti

Malvezzi

R.A.

Manzoni

Menasce

Moroni

Paganoni

Pauwels

Pedrini

Pigazzini

Ragazzi

Redaelli

Tabarelli de Fatis

aINFN Sezione di Milano-Bicocca, Milano, ItalyINFN Sezione di Milano-BicoccaMilanoItalybUniversità di Milano-Bicocca, Milano, ItalyUniversità di Milano-BicoccaMilanoItaly28

Also at INFN Sezione di Milano-Bicocca; Università di Milano-Bicocca, Milano, Italy.

Buontempo

Cavallo

Di Guida

Fabozzi

Fienga

A.O.M.

Iorio

W.A.

Khan

Lista

Meola

Paolucci

Sciacca

Thyssen

aINFN Sezione di Napoli, Napoli, ItalyINFN Sezione di NapoliNapoliItalybUniversità di Napoli ‘Federico II’, Napoli, ItalyUniversità di Napoli ‘Federico II’NapoliItalycUniversità della Basilicata, Potenza, ItalyUniversità della BasilicataPotenzaItalydUniversità G. Marconi, Roma, ItalyUniversità G. MarconiRomaItaly

Azzi

Bacchetta

Benato

Bisello

Boletti

Bragagnolo

Carlin

Carvalho Antunes De Oliveira

Checchia

Dall'Osso

De Castro Manzano

Dorigo

Dosselli

Gasparini

Lacaprara

Lujan

Margoni

A.T.

Meneguzzo

Pozzobon

Ronchese

Rossin

Simonetto

Torassa

Ventura

Zanetti

Zotto

aINFN Sezione di Padova, Padova, ItalyINFN Sezione di PadovaPadovaItalybUniversità di Padova, Padova, ItalyUniversità di PadovaPadovaItalycUniversità di Trento, Trento, ItalyUniversità di TrentoTrentoItaly

Braghieri

Magnani

Montagna

S.P.

Ratti

Ressegotti

Riccardi

Salvini

Vai

Vitulo

aINFN Sezione di Pavia, Pavia, ItalyINFN Sezione di PaviaPaviaItalybUniversità di Pavia, Pavia, ItalyUniversità di PaviaPaviaItaly

Alunni Solestizi

Biasini

G.M.

Bilei

Cecchi

Ciangottini

Fanò

Lariccia

Leonardi

Manoni

Mantovani

Mariani

Menichelli

Rossi

Santocchia

Spiga

aINFN Sezione di Perugia, Perugia, ItalyINFN Sezione di PerugiaPerugiaItalybUniversità di Perugia, Perugia, ItalyUniversità di PerugiaPerugiaItaly

Androsov

Azzurri

Bagliesi

Boccali

Borrello

Castaldi

M.A.

Ciocci

Dell'Orso

Fedi

Giannini

Giassi

M.T.

Grippo

Ligabue

Lomtadze

Manca

Mandorli

Martini

Messineo

Palla

Rizzi

Savoy-Navarro

Spagnolo

Tenchini

Tonelli

Venturi

P.G.

Verdini

aINFN Sezione di Pisa, Pisa, ItalyINFN Sezione di PisaPisaItalybUniversità di Pisa, Pisa, ItalyUniversità di PisaPisaItalycScuola Normale Superiore di Pisa, Pisa, ItalyScuola Normale Superiore di PisaPisaItaly29

Also at Purdue University, West Lafayette, USA.

Barone

Cavallari

Cipriani

Daci

Del Re

Di Marco

Diemoz

Gelli

Longo

Margaroli

Marzocchi

Meridiani

Organtini

Paramatti

Preiato

Rahatlou

Rovelli

Santanastasio

aINFN Sezione di Roma, Rome, ItalyINFN Sezione di RomaRomeItalybSapienza Università di Roma, Rome, ItalySapienza Università di RomaRomeItaly

Amapane

Arcidiacono

Argiro

Arneodo

Bartosik

Bellan

Biino

Cartiglia

Cenna

Costa

Covarelli

Degano

Demaria

Kiani

Mariotti

Maselli

Migliore

Monaco

Monteil

Monteno

M.M.

Obertino

Pacher

Pastrone

Pelliccioni

G.L.

Pinna Angioni

Ravera

Romero

Ruspa

Sacchi

Shchelina

Sola

Solano

Staiano

Traczyk

aINFN Sezione di Torino, Torino, ItalyINFN Sezione di TorinoTorinoItalybUniversità di Torino, Torino, ItalyUniversità di TorinoTorinoItalycUniversità del Piemonte Orientale, Novara, ItalyUniversità del Piemonte OrientaleNovaraItaly

Belforte

Casarsa

Cossutti

Della Ricca

Zanetti

aINFN Sezione di Trieste, Trieste, ItalyINFN Sezione di TriesteTriesteItalybUniversità di Trieste, Trieste, ItalyUniversità di TriesteTriesteItaly

D.H.

Kim

G.N.

Kim

M.S.

Kim

Lee

S.W.

Lee

C.S.

Moon

Y.D.

Sekmen

D.C.

Son

Y.C.

YangKyungpook National University, Daegu, Republic of KoreaKyungpook National UniversityDaeguRepublic of Korea

LeeChonbuk National University, Jeonju, Republic of KoreaChonbuk National UniversityJeonjuRepublic of Korea

Kim

D.H.

Moon

OhChonnam National University, Institute for Universe and Elementary Particles, Kwangju, Republic of KoreaChonnam National UniversityInstitute for Universe and Elementary ParticlesKwangjuRepublic of Korea

J.A.

Brochero Cifuentes

Goh

T.J.

KimHanyang University, Seoul, Republic of KoreaHanyang UniversitySeoulRepublic of Korea

Cho

Choi

Gyun

Hong

Kim

Lee

K.S.

Lee

Lim

S.K.

Park

RohKorea University, Seoul, Republic of KoreaKorea UniversitySeoulRepublic of Korea

Almond

Kim

J.S.

Kim

Lee

Nam

S.B.

B.C.

Radburn-Smith

S.h.

Seo

U.K.

Yang

H.D.

Yoo

G.B.

YuSeoul National University, Seoul, Republic of KoreaSeoul National UniversitySeoulRepublic of Korea

Choi

Kim

J.H.

Kim

J.S.H.

Lee

I.C.

ParkUniversity of Seoul, Seoul, Republic of KoreaUniversity of SeoulSeoulRepublic of Korea

Choi

Hwang

Lee

YuSungkyunkwan University, Suwon, Republic of KoreaSungkyunkwan UniversitySuwonRepublic of Korea

Dudenas

Juodagalvis

VaitkusVilnius University, Vilnius, LithuaniaVilnius UniversityVilniusLithuania

Ahmed

Z.A.

Ibrahim

M.A.B.

Md Ali

Mohamad Idris

W.A.T.

Wan Abdullah

M.N.

Yusli

ZolkapliNational Centre for Particle Physics, Universiti Malaya, Kuala Lumpur, MalaysiaNational Centre for Particle PhysicsUniversiti MalayaKuala LumpurMalaysia30

Also at International Islamic University of Malaysia, Kuala Lumpur, Malaysia.

Also at Malaysian Nuclear Agency, MOSTI, Kajang, Malaysia.

Reyes-Almanza

Ramirez-Sanchez

M.C.

Duran-Osuna

Castilla-Valdez

De La Cruz-Burelo

Heredia-De La Cruz

R.I.

Rabadan-Trejo

Lopez-Fernandez

Mejia Guisao

Sanchez-HernandezCentro de Investigacion y de Estudios Avanzados del IPN, Mexico City, MexicoCentro de Investigacion y de Estudios Avanzados del IPNMexico CityMexico32

Also at Consejo Nacional de Ciencia y Tecnología, Mexico city, Mexico.

Carrillo Moreno

Oropeza Barrera

Vazquez ValenciaUniversidad Iberoamericana, Mexico City, MexicoUniversidad IberoamericanaMexico CityMexico

Pedraza

H.A.

Salazar Ibarguen

Uribe EstradaBenemerita Universidad Autonoma de Puebla, Puebla, MexicoBenemerita Universidad Autonoma de PueblaPueblaMexico

Morelos PinedaUniversidad Autónoma de San Luis Potosí, San Luis Potosí, MexicoUniversidad Autónoma de San Luis PotosíSan Luis PotosíMexico

KrofcheckUniversity of Auckland, Auckland, New ZealandUniversity of AucklandAucklandNew Zealand

P.H.

ButlerUniversity of Canterbury, Christchurch, New ZealandUniversity of CanterburyChristchurchNew Zealand

Ahmad

Hassan

H.R.

Hoorani

Saddique

M.A.

Shah

Shoaib

WaqasNational Centre for Physics, Quaid-I-Azam University, Islamabad, PakistanNational Centre for PhysicsQuaid-I-Azam UniversityIslamabadPakistan

Bialkowska

Bluj

Boimska

Frueboes

Górski

Kazana

Nawrocki

Szleper

ZalewskiNational Centre for Nuclear Research, Swierk, PolandNational Centre for Nuclear ResearchSwierkPoland

Bunkowski

Byszuk

Doroba

Kalinowski

Konecki

Krolikowski

Misiura

Olszewski

Pyskir

WalczakInstitute of Experimental Physics, Faculty of Physics, University of Warsaw, Warsaw, PolandInstitute of Experimental PhysicsFaculty of PhysicsUniversity of WarsawWarsawPoland33

Also at Warsaw University of Technology, Institute of Electronic Systems, Warsaw, Poland.

Bargassa

Beirão Da Cruz E Silva

Di Francesco

Faccioli

Galinhas

Gallinaro

Hollar

Leonardo

Lloret Iglesias

M.V.

Nemallapudi

Seixas

Strong

Toldaiev

Vadruccio

VarelaLaboratório de Instrumentação e Física Experimental de Partículas, Lisboa, PortugalLaboratório de Instrumentação e Física Experimental de PartículasLisboaPortugal

Afanasiev

Bunin

Gavrilenko

Golutvin

Gorbunov

Kamenev

Karjavin

Lanev

Malakhov

Matveev

Palichik

Perelygin

Shmatov

Shulha

Skatchkov

Smirnov

Voytishin

ZarubinJoint Institute for Nuclear Research, Dubna, RussiaJoint Institute for Nuclear ResearchDubnaRussia34

Also at Institute for Nuclear Research, Moscow, Russia.

Now at National Research Nuclear University ‘Moscow Engineering Physics Institute’ (MEPhI), Moscow, Russia.

Ivanov

Kim

Kuznetsova

Levchenko

Murzin

Oreshkin

Smirnov

Sulimov

Uvarov

Vavilov

VorobyevPetersburg Nuclear Physics Institute, Gatchina (St. Petersburg), RussiaPetersburg Nuclear Physics InstituteGatchina (St. Petersburg)Russia36

Also at St. Petersburg State Polytechnical University, St. Petersburg, Russia.

Also at University of Florida, Gainesville, USA.

Yu.

Andreev

Dermenev

Gninenko

Golubev

Karneyeu

Kirsanov

Krasnikov

Pashenkov

Tlisov

ToropinInstitute for Nuclear Research, Moscow, RussiaInstitute for Nuclear ResearchMoscowRussia

Epshteyn

Gavrilov

Lychkovskaya

Popov

Pozdnyakov

Safronov

Spiridonov

Stepennov

Toms

Vlasov

ZhokinInstitute for Theoretical and Experimental Physics, Moscow, RussiaInstitute for Theoretical and Experimental PhysicsMoscowRussia

Aushev

Bylinkin

Moscow Institute of Physics and Technology, Moscow, RussiaMoscow Institute of Physics and TechnologyMoscowRussia

Chadeeva

Parygin

Philippov

Polikarpov

Popova

RusinovNational Research Nuclear University ‘Moscow Engineering Physics Institute’ (MEPhI), Moscow, RussiaNational Research Nuclear University ‘Moscow Engineering Physics Institute’ (MEPhI)MoscowRussia38

Also at P.N. Lebedev Physical Institute, Moscow, Russia.

Andreev

Azarkin

Dremin

Kirakosyan

TerkulovP.N. Lebedev Physical Institute, Moscow, RussiaP.N. Lebedev Physical InstituteMoscowRussia

Baskakov

Belyaev

Boos

Bunichev

Dubinin

Dudko

Ershov

Gribushin

Klyukhin

Kodolova

Lokhtin

Miagkov

Obraztsov

Petrushanko

SavrinSkobeltsyn Institute of Nuclear Physics, Lomonosov Moscow State University, Moscow, RussiaSkobeltsyn Institute of Nuclear PhysicsLomonosov Moscow State UniversityMoscowRussia39

Also at California Institute of Technology, Pasadena, USA.

Blinov

Skovpen

Shtol

Novosibirsk State University (NSU), Novosibirsk, RussiaNovosibirsk State University (NSU)NovosibirskRussia40

Also at Budker Institute of Nuclear Physics, Novosibirsk, Russia.

Azhgirey

Bayshev

Bitioukov

Elumakhov

Kachanov

Kalinin

Konstantinov

Petrov

Ryutin

Sobol

Troshin

Tyurin

Uzunian

VolkovState Research Center of Russian Federation, Institute for High Energy Physics, Protvino, RussiaState Research Center of Russian FederationInstitute for High Energy PhysicsProtvinoRussia

Adzic

Cirkovic

Devetak

Dordevic

Milosevic

RekovicUniversity of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, SerbiaUniversity of BelgradeFaculty of PhysicsVinca Institute of Nuclear SciencesBelgradeSerbia41

Also at Faculty of Physics, University of Belgrade, Belgrade, Serbia.

Alcaraz Maestre

Barrio Luna

Cerrada

Colino

De La Cruz

Delgado Peris

Escalante Del Valle

Fernandez Bedoya

J.P.

Fernández Ramos

Flix

M.C.

Fouz

Garcia-Abia

Gonzalez Lopez

Goy Lopez

J.M.

Hernandez

M.I.

Josa

Moran

Pérez-Calero Yzquierdo

Puerta Pelayo

Quintario Olmeda

Redondo

Romero

M.S.

Soares

Álvarez FernándezCentro de Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT), Madrid, SpainCentro de Investigaciones Energéticas Medioambientales y Tecnológicas (CIEMAT)MadridSpain

J.F.

de Trocóniz

MissiroliUniversidad Autónoma de Madrid, Madrid, SpainUniversidad Autónoma de MadridMadridSpain

Cuevas

Erice

Fernandez Menendez

Gonzalez Caballero

J.R.

González Fernández

Palencia Cortezon

Sanchez Cruz

Vischia

J.M.

Vizan GarciaUniversidad de Oviedo, Oviedo, SpainUniversidad de OviedoOviedoSpain

I.J.

Cabrillo

Calderon

Chazin Quero

Curras

Duarte Campderros

Fernandez

Garcia-Ferrero

Gomez

Lopez Virto

Marco

Martinez Rivero

Martinez Ruiz del Arbol

Matorras

Piedra Gomez

Rodrigo

Ruiz-Jimeno

Scodellaro

Trevisani

Vila

Vilar CortabitarteInstituto de Física de Cantabria (IFCA), CSIC-Universidad de Cantabria, Santander, SpainInstituto de Física de Cantabria (IFCA)CSIC-Universidad de CantabriaSantanderSpain

Abbaneo

Auffray

Baillon

A.H.

Ball

Barney

Bianco

Bloch

Bocci

Botta

Camporesi

Castello

Cepeda

Cerminara

Chapon

Chen

d'Enterria

Dabrowski

Daponte

David

De Gruttola

De Roeck

Dobson

Dorney

du Pree

Dünser

Dupont

Elliott-Peisert

Everaerts

Fallavollita

Franzoni

Fulcher

Funk

Gigi

Gilbert

Gill

Glege

Gulhan

Harris

Hegeman

Innocente

Janot

Karacheban

Kieseler

Kirschenmann

Knünz

Kornmayer

M.J.

Kortelainen

Krammer

Lange

Lecoq

Lourenço

M.T.

Lucchini

Malgeri

Mannelli

Martelli

Meijers

J.A.

Merlin

Mersi

Meschi

Milenovic

Moortgat

Mulders

Neugebauer

Ngadiuba

Orfanelli

Orsini

Pape

Perez

Peruzzi

Petrilli

Petrucciani

Pfeiffer

Pierini

Racz

Reis

Rolandi

Rovere

Sakulin

Schäfer

Schwick

Seidel

Selvaggi

Sharma

Silva

Sphicas

Stakia

Steggemann

Stoye

Tosi

Treille

Triossi

Tsirou

Veckalns

Verweij

W.D.

ZeunerCERN, European Organization for Nuclear Research, Geneva, SwitzerlandCERNEuropean Organization for Nuclear ResearchGenevaSwitzerland42

Also at University of Belgrade, Faculty of Physics and Vinca Institute of Nuclear Sciences, Belgrade, Serbia.

Also at Scuola Normale e Sezione dell'INFN, Pisa, Italy.

Also at National and Kapodistrian University of Athens, Athens, Greece.

Also at Riga Technical University, Riga, Latvia.

Bertl

†

Caminada

Deiters

Erdmann

Horisberger

Ingram

H.C.

Kaestli

Kotlinski

Langenegger

Rohe

S.A.

WiederkehrPaul Scherrer Institut, Villigen, SwitzerlandPaul Scherrer InstitutVilligenSwitzerland†

Deceased.

Also at Universität Zürich, Zurich, Switzerland.

Bäni

Berger

Bianchini

Casal

Dissertori

Dittmar

Donegà

Grab

Heidegger

Hits

Hoss

Kasieczka

Klijnsma

Lustermann

Mangano

Marionneau

M.T.

Meinhard

Meister

Micheli

Musella

Nessi-Tedaldi

Pandolfi

Pata

Pauss

Perrin

Perrozzi

Quittnat

Reichmann

Schönenberger

Shchutska

V.R.

Tavolaro

Theofilatos

M.L.

Vesterbacka Olsson

Wallny

D.H.

ZhuInstitute for Particle Physics, ETH Zurich, Zurich, SwitzerlandInstitute for Particle PhysicsETH ZurichZurichSwitzerland

T.K.

Aarrestad

Amsler

M.F.

Canelli

De Cosa

Del Burgo

Donato

Galloni

Hreus

Kilminster

Pinna

Rauco

Robmann

Salerno

Seitz

Takahashi

ZucchettaUniversität Zürich, Zurich, SwitzerlandUniversität ZürichZurichSwitzerland47

Also at Stefan Meyer Institute for Subatomic Physics (SMI), Vienna, Austria.

Candelise

T.H.

Doan

Sh.

Jain

Khurana

C.M.

Kuo

Lin

Pozdnyakov

S.S.

YuNational Central University, Chung-Li, TaiwanNational Central UniversityChung-LiTaiwan

Arun

Kumar

Chang

Chao

K.F.

Chen

P.H.

Chen

Fiori

Hsiung

Y.F.

Liu

R.-S.

Paganis

Psallidas

Steen

J.f.

TsaiNational Taiwan University (NTU), Taipei, TaiwanNational Taiwan University (NTU)TaipeiTaiwan

Asavapibhop

Kovitanggoon

Singh

SrimanobhasChulalongkorn University, Faculty of Science, Department of Physics, Bangkok, ThailandChulalongkorn UniversityFaculty of ScienceDepartment of PhysicsBangkokThailand

Boran

Cerci

Damarseckin

Z.S.

Demiroglu

Dozen

Dumanoglu

Girgis

Gokbulut

Guler

Hos

E.E.

Kangal

Kara

Kayis Topaksu

Kiminsu

Oglakci

Onengut

Ozdemir

Sunar Cerci

Tali

Turkcapar

I.S.

Zorbakir

ZorbilmezÇukurova University, Physics Department, Science and Art Faculty, Adana, TurkeyÇukurova UniversityPhysics DepartmentScience and Art FacultyAdanaTurkey48

Also at Adiyaman University, Adiyaman, Turkey.

Also at Istanbul Aydin University, Istanbul, Turkey.

Also at Mersin University, Mersin, Turkey.

Also at Cag University, Mersin, Turkey.

Also at Piri Reis University, Istanbul, Turkey.

Bilin

Karapinar

Ocalan

Yalvac

ZeyrekMiddle East Technical University, Physics Department, Ankara, TurkeyMiddle East Technical UniversityPhysics DepartmentAnkaraTurkey53

Also at Izmir Institute of Technology, Izmir, Turkey.

Also at Necmettin Erbakan University, Konya, Turkey.

Gülmez

Kaya

Tekten

E.A.

Yetkin

Bogazici University, Istanbul, TurkeyBogazici UniversityIstanbulTurkey55

Also at Marmara University, Istanbul, Turkey.

Also at Kafkas University, Kars, Turkey.

Also at Istanbul Bilgi University, Istanbul, Turkey.

M.N.

Agaras

Atay

Cakir

CankocakIstanbul Technical University, Istanbul, TurkeyIstanbul Technical UniversityIstanbulTurkey

GrynyovInstitute for Scintillation Materials of National Academy of Science of Ukraine, Kharkov, UkraineInstitute for Scintillation Materials of National Academy of Science of UkraineKharkovUkraine

LevchukNational Scientific Center, Kharkov Institute of Physics and Technology, Kharkov, UkraineNational Scientific CenterKharkov Institute of Physics and TechnologyKharkovUkraine

Aggleton

Ball

Beck

J.J.

Brooke

Burns

Clement

Cussans

Davignon

Flacher

Goldstein

Grimes

G.P.

Heath

H.F.

Heath

Jacob

Kreczko

Lucas

D.M.

Newbold

Paramesvaran

Poll

Sakuma

Seif El Nasr-storey

Smith

V.J.

SmithUniversity of Bristol, Bristol, United KingdomUniversity of BristolBristolUnited Kingdom58

Also at Rutherford Appleton Laboratory, Didcot, United Kingdom.

K.W.

Bell

Belyaev

Brew

R.M.

Brown

Calligaris

Cieri

D.J.A.

Cockerill

J.A.

Coughlan

Harder

Harper

Olaiya

Petyt

C.H.

Shepherd-Themistocleous

Thea

I.R.

Tomalin

WilliamsRutherford Appleton Laboratory, Didcot, United KingdomRutherford Appleton LaboratoryDidcotUnited Kingdom59

Also at School of Physics and Astronomy, University of Southampton, Southampton, United Kingdom.

Auzinger

Bainbridge

Borg

Breeze

Buchmuller

Bundock

Casasso

Citron

Colling

Corpe

Dauncey

Davies

De Wit

Della Negra

Di Maria

Elwood

Haddad

Hall

Iles

James

Lane

Laner

Lyons

A.-M.

Magnan

Malik

Mastrolorenzo

Matsushita

Nash

Nikitenko

Palladino

Pesaresi

D.M.

Raymond

Richards

Rose

Scott

Seez

Shtipliyski

Summers

Tapper

Uchida

Vazquez Acosta

Virdee

Wardle

Winterbottom

Wright

S.C.

ZenzImperial College, London, United KingdomImperial CollegeLondonUnited Kingdom60

Also at Instituto de Astrofísica de Canarias, La Laguna, Spain.

J.E.

Cole

P.R.

Hobson

Khan

Kyberd

I.D.

Reid

Symonds

Teodorescu

TurnerBrunel University, Uxbridge, United KingdomBrunel UniversityUxbridgeUnited Kingdom

Borzou

Call

Dittmann

Hatakeyama

Liu

Pastika

SmithBaylor University, Waco, USABaylor UniversityWacoUSA

Bartek

DominguezCatholic University of America, Washington DC, USACatholic University of AmericaWashingtonDCUSA

Buccilli

S.I.

Cooper

Henderson

Rumerio

WestThe University of Alabama, Tuscaloosa, USAThe University of AlabamaTuscaloosaUSA

Arcaro

Avetisyan

Bose

Gastler

Rankin

Richardson

Rohlf

Sulak

ZouBoston University, Boston, USABoston UniversityBostonUSA

Benelli

Cutts

Garabedian

Hakala

Heintz

J.M.

Hogan

K.H.M.

Kwok

Laird

Landsberg

Mao

Narain

Pazzini

Piperov

Sagir

Syarif

YuBrown University, Providence, USABrown UniversityProvidenceUSA

Band

Brainerd

Burns

Calderon De La Barca Sanchez

Chertok

Conway

P.T.

Cox

Erbacher

Flores

Funk

Gardner

Lander

Mclean

Mulhearn

Pellett

Pilot

Shalhout

Shi

Smith

Stolp

Tos

Tripathi

WangUniversity of California, Davis, Davis, USAUniversity of California, DavisDavisUSA

Bachtis

Bravo

Cousins

Dasgupta

Florent

Hauser

Ignatenko

Mccoll

Regnard

Saltzberg

Schnaible

ValuevUniversity of California, Los Angeles, USAUniversity of CaliforniaLos AngelesUSA

Bouvier

Burt

Clare

Ellison

J.W.

Gary

S.M.A.

Ghiasi Shirazi

Hanson

Heilman

Jandir

Kennedy

Lacroix

O.R.

Long

Olmedo Negrete

M.I.

Paneva

Shrinivas

Wang

Wei

Wimpenny

B.R.

YatesUniversity of California, Riverside, Riverside, USAUniversity of California, RiversideRiversideUSA

J.G.

Branson

Cittolin

Derdzinski

Gerosa

Hashemi

Holzner

Klein

Kole

Krutelyov

Letts

Macneill

Masciovecchio

Olivito

Padhi

Pieri

Sani

Sharma

Simon

Tadel

Vartak

Wasserbaech

Wood

Würthwein

Yagil

Zevi Della PortaUniversity of California, San Diego, La Jolla, USAUniversity of California, San DiegoLa JollaUSA61

Also at Utah Valley University, Orem, USA.

Amin

Bhandari

Bradmiller-Feld

Campagnari

Dishaw

Dutta

Franco Sevilla

George

Golf

Gouskos

Gran

Heller

Incandela

S.D.

Mullin

Ovcharova

Richman

Stuart

Suarez

YooUniversity of California, Santa Barbara – Department of Physics, Santa Barbara, USAUniversity of California, Santa BarbaraDepartment of PhysicsSanta BarbaraUSA

Anderson

Bendavid

Bornheim

J.M.

Lawhorn

H.B.

Newman

Nguyen

Pena

Spiropulu

J.R.

Vlimant

Xie

Zhang

R.Y.

ZhuCalifornia Institute of Technology, Pasadena, USACalifornia Institute of TechnologyPasadenaUSA

M.B.

Andrews

Ferguson

Mudholkar

Paulini

Russ

Sun

Vogel

Vorobiev

WeinbergCarnegie Mellon University, Pittsburgh, USACarnegie Mellon UniversityPittsburghUSA

J.P.

Cumalat

W.T.

Ford

Jensen

Johnson

Krohn

Leontsinis

Mulholland

Stenson

S.R.

WagnerUniversity of Colorado Boulder, Boulder, USAUniversity of Colorado BoulderBoulderUSA

Alexander

Chaves

Chu

Dittmer

Mcdermott

Mirman

J.R.

Patterson

Rinkevicius

Ryd

Skinnari

Soffi

S.M.

Tan

Tao

Thom

Tucker

Wittich

ZientekCornell University, Ithaca, USACornell UniversityIthacaUSA

Abdullin

Albrow

Alyari

Apollinari

Apresyan

Apyan

Banerjee

L.A.T.

Bauerdick

Beretvas

Berryhill

P.C.

Bhat

Bolla

†

Burkett

J.N.

Butler

Canepa

G.B.

Cerati

H.W.K.

Cheung

Chlebana

Cremonesi

Duarte

V.D.

Elvira

Freeman

Gecse

Gottschalk

Gray

Green

Grünendahl

Gutsche

R.M.

Harris

Hasegawa

Hirschauer

Jayatilaka

Jindariani

Johnson

Joshi

Klima

Kreis

Lammel

Lincoln

Lipton

Liu

Lopes De Sá

Lykken

Maeshima

Magini

J.M.

Marraffino

Maruyama

Mason

McBride

Merkel

Mrenna

Nahn

O'Dell

Pedro

Prokofyev

Rakness

Ristori

Schneider

Sexton-Kennedy

Soha

W.J.

Spalding

Spiegel

Stoynev

Strait

Strobbe

Taylor

Tkaczyk

N.V.

Tran

Uplegger

E.W.

Vaandering

Vernieri

Verzocchi

Vidal

Wang

H.A.

Weber

WhitbeckFermi National Accelerator Laboratory, Batavia, USAFermi National Accelerator LaboratoryBataviaUSA

Acosta

Avery

Bortignon

Bourilkov

Brinkerhoff

Carnes

Carver

Curry

R.D.

Field

I.K.

Furic

Konigsberg

Korytov

Kotov

Matchev

Mei

Mitselmakher

Rank

Sperka

Terentyev

Thomas

Wang

YeltonUniversity of Florida, Gainesville, USAUniversity of FloridaGainesvilleUSA

Y.R.

Joshi

Linn

Markowitz

J.L.

RodriguezFlorida International University, Miami, USAFlorida International UniversityMiamiUSA

Ackert

Adams

Askew

Hagopian

K.F.

Johnson

Kolberg

Martinez

Perry

Prosper

Saha

Santra

Sharma

YohayFlorida State University, Tallahassee, USAFlorida State UniversityTallahasseeUSA

M.M.

Baarmand

Bhopatkar

Colafranceschi

Hohlmann

Noonan

Roy

YumicevaFlorida Institute of Technology, Melbourne, USAFlorida Institute of TechnologyMelbourneUSA

M.R.

Adams

Apanasevich

Berry

R.R.

Betts

Cavanaugh

Chen

Evdokimov

C.E.

Gerber

D.A.

Hangal

D.J.

Hofman

Jung

Kamin

I.D.

Sandoval Gonzalez

M.B.

Tonjes

Trauger

Varelas

Wang

ZhangUniversity of Illinois at Chicago (UIC), Chicago, USAUniversity of Illinois at Chicago (UIC)ChicagoUSA

Bilki

Clarida

Dilsiz

Durgut

R.P.

Gandrajula

Haytmyradov

Khristenko

J.-P.

Merlo

Mermerkaya

Mestvirishvili

Moeller

Nachtman

Ogul

Onel

Ozok

Penzo

Snyder

Tiras

Wetzel

YiThe University of Iowa, Iowa City, USAThe University of IowaIowa CityUSA62

Also at Beykent University, Istanbul, Turkey.

Also at Bingol University, Bingol, Turkey.

Also at Erzincan University, Erzincan, Turkey.

Also at Sinop University, Sinop, Turkey.

Also at Mimar Sinan University, Istanbul, Istanbul, Turkey.

Blumenfeld

Cocoros

Eminizer

Fehling

Feng

A.V.

Gritsan

Maksimovic

Roskes

Sarica

Swartz

Xiao

YouJohns Hopkins University, Baltimore, USAJohns Hopkins UniversityBaltimoreUSA

Al-bataineh

Baringer

Bean

Boren

Bowen

Castle

Khalil

Kropivnitskaya

Majumder

Mcbrayer

Murray

Royon

Sanders

Schmitz

J.D.

Tapia Takaki

WangThe University of Kansas, Lawrence, USAThe University of KansasLawrenceUSA

Ivanov

Kaadze

Maravin

Mohammadi

L.K.

Saini

Skhirtladze

TodaKansas State University, Manhattan, USAKansas State UniversityManhattanUSA

Rebassoo

WrightLawrence Livermore National Laboratory, Livermore, USALawrence Livermore National LaboratoryLivermoreUSA

Anelli

Baden

Baron

Belloni

Calvert

S.C.

Eno

Ferraioli

N.J.

Hadley

Jabeen

G.Y.

Jeng

R.G.

Kellogg

Kunkle

A.C.

Mignerey

Ricci-Tam

Y.H.

Shin

Skuja

S.C.

TonwarUniversity of Maryland, College Park, USAUniversity of MarylandCollege ParkUSA

Abercrombie

Allen

Azzolini

Barbieri

Baty

Brandt

Busza

I.A.

Cali

D'Alfonso

Demiragli

Gomez Ceballos

Goncharov

Hsu

Iiyama

G.M.

Innocenti

Klute

Kovalskyi

Y.S.

Lai

Y.-J.

Lee

Levin

P.D.

Luckey

Maier

A.C.

Marini

Mcginn

Mironov

Narayanan

Niu

Paus

Roland

Salfeld-Nebgen

G.S.F.

Stephans

Tatar

Velicanu

Wang

T.W.

Wang

WyslouchMassachusetts Institute of Technology, Cambridge, USAMassachusetts Institute of TechnologyCambridgeUSA

A.C.

Benvenuti

R.M.

Chatterjee

Evans

Hansen

Kalafut

Kubota

Lesko

Mans

Nourbakhsh

Ruckstuhl

Rusack

TurkewitzUniversity of Minnesota, Minneapolis, USAUniversity of MinnesotaMinneapolisUSA

J.G.

Acosta

OliverosUniversity of Mississippi, Oxford, USAUniversity of MississippiOxfordUSA

Avdeeva

Bloom

D.R.

Claes

Fangmeier

Gonzalez Suarez

Kamalieddin

Kravchenko

Monroy

J.E.

Siado

G.R.

Snow

StiegerUniversity of Nebraska-Lincoln, Lincoln, USAUniversity of Nebraska-LincolnLincolnUSA

Dolen

Godshalk

Harrington

Iashvili

Nguyen

Parker

Rappoccio

RoozbahaniState University of New York at Buffalo, Buffalo, USAState University of New York at BuffaloBuffaloUSA

Alverson

Barberis

Hortiangtham

Massironi

D.M.

Morse

Nash

Orimoto

Teixeira De Lima

Trocino

WoodNortheastern University, Boston, USANortheastern UniversityBostonUSA

Bhattacharya

Charaf

K.A.

Hahn

Mucia

Odell

Pollack

M.H.

Schmitt

Sung

Trovato

VelascoNorthwestern University, Evanston, USANorthwestern UniversityEvanstonUSA

Dev

Hildreth

Hurtado Anampa

Jessop

D.J.

Karmgard

Kellams

Lannon

Loukas

Marinelli

Meng

Mueller

Musienko

Planer

Reinsvold

Ruchti

Smith

Taroni

Wayne

Wolf

WoodardUniversity of Notre Dame, Notre Dame, USAUniversity of Notre DameNotre DameUSA

Alimena

Antonelli

Bylsma

L.S.

Durkin

Flowers

Francis

Hart

Hill

Liu

Luo

Puigh

B.L.

Winer

H.W.

WulsinThe Ohio State University, Columbus, USAThe Ohio State UniversityColumbusUSA

Cooperstein

Driga

Elmer

Hardenbrook

Hebda

Higginbotham

Lange

Luo

Marlow

Mei

Ojalvo

Olsen

Palmer

Piroué

Stickland

TullyPrinceton University, Princeton, USAPrinceton UniversityPrincetonUSA

Malik

NorbergUniversity of Puerto Rico, Mayaguez, USAUniversity of Puerto RicoMayaguezUSA

Barker

V.E.

Barnes

Das

Folgueras

Gutay

M.K.

Jha

Jones

A.W.

Jung

Khatiwada

D.H.

Miller

Neumeister

C.C.

Peng

J.F.

Schulte

Sun

Wang

XiePurdue University, West Lafayette, USAPurdue UniversityWest LafayetteUSA

Cheng

Parashar

StupakPurdue University Northwest, Hammond, USAPurdue University NorthwestHammondUSA

Adair

Akgun

Chen

K.M.

Ecklund

F.J.M.

Geurts

Guilbaud

Michlin

Northup

B.P.

Padley

Roberts

Rorie

ZabelRice University, Houston, USARice UniversityHoustonUSA

Bodek

de Barbaro

Demina

Y.t.

Duh

Ferbel

Galanti

Garcia-Bellido

Han

Hindrichs

Khukhunaishvili

K.H.

Tan

VerzettiUniversity of Rochester, Rochester, USAUniversity of RochesterRochesterUSA

Ciesielski

Goulianos

MesropianThe Rockefeller University, New York, USAThe Rockefeller UniversityNew YorkUSA

Agapitos

J.P.

Chou

Gershtein

T.A.

Gómez Espinosa

Halkiadakis

Heindl

Hughes

Kaplan

Kunnawalkam Elayavalli

Kyriacou

Lath

Montalvo

Nash

Osherson

Saka

Salur

Schnetzer

Sheffield

Somalwar

Stone

Thomas

Thomassen

WalkerRutgers, The State University of New Jersey, Piscataway, USARutgers, The State University of New JerseyPiscatawayUSA

A.G.

Delannoy

Foerster

Heideman

Riley

Rose

Spanier

ThapaUniversity of Tennessee, Knoxville, USAUniversity of TennesseeKnoxvilleUSA

Bouhali

Castaneda Hernandez

Celik

Dalchenko

De Mattia

Delgado

Dildick

Eusebi

Gilmore

Huang

Kamon

Mueller

Pakhotin

Patel

Perloff

Perniè

Rathjens

Safonov

Tatarinov

K.A.

UlmerTexas A&M University, College Station, USATexas A&M UniversityCollege StationUSA67

Also at Texas A&M University at Qatar, Doha, Qatar.

Also at Kyungpook National University, Daegu, Korea.

Akchurin

Damgov

De Guio

P.R.

Dudero

Faulkner

Gurpinar

Kunori

Lamichhane

S.W.

Lee

Libeiro

Peltola

Undleeb

Volobouev

WangTexas Tech University, Lubbock, USATexas Tech UniversityLubbockUSA

Greene

Gurrola

Janjam

Johns

Maguire

Melo

Padeken

Sheldon

Tuo

Velkovska

XuVanderbilt University, Nashville, USAVanderbilt UniversityNashvilleUSA

M.W.

Arenton

Barria

Cox

Hirosky

Joyce

Ledovskoy

Neu

Sinthuprasith

Wang

Wolfe

XiaUniversity of Virginia, Charlottesville, USAUniversity of VirginiaCharlottesvilleUSA

Harr

P.E.

Karchin

Sturdy

ZaleskiWayne State University, Detroit, USAWayne State UniversityDetroitUSA

Brodski

Buchanan

Caillol

Dasu

Dodd

Duric

Gomber

Grothe

Herndon

Hervé

Hussain

Klabbers

Lanaro

Levine

Long

Loveless

G.A.

Pierro

Polese

Ruggles

Savin

Smith

W.H.

Smith

Taylor

WoodsUniversity of Wisconsin – Madison, Madison, WI, USAUniversity of Wisconsin – MadisonMadisonWIUSA

CERN, SwitzerlandCERNSwitzerland⋆

E-mail address: cms-publication-committee-chair@cern.ch.

Editor: M. Doser

Abstract

A measurement of the H→ττ signal strength is performed using events recorded in proton–proton collisions by the CMS experiment at the LHC in 2016 at a center-of-mass energy of 13TeV. The data set corresponds to an integrated luminosity of 35.9fb−1. The H→ττ signal is established with a significance of 4.9 standard deviations, to be compared to an expected significance of 4.7 standard deviations. The best fit of the product of the observed H→ττ signal production cross section and branching fraction is 1.09−0.26+0.27 times the standard model expectation. The combination with the corresponding measurement performed with data collected by the CMS experiment at center-of-mass energies of 7 and 8TeV leads to an observed significance of 5.9 standard deviations, equal to the expected significance. This is the first observation of Higgs boson decays to τ leptons by a single experiment.

Keywords

CMSPhysicsTauHiggsObservationLHC1

Introduction

In the standard model (SM) of particle physics [1–3], electroweak symmetry breaking is achieved via the Brout–Englert–Higgs mechanism [4–9], leading, in its minimal version, to the prediction of the existence of one physical neutral scalar particle, commonly known as the Higgs boson (H). A particle compatible with such a boson was observed by the ATLAS and CMS experiments at the CERN LHC in the ZZ, γγ, and W+W− decay channels [10–12], during the proton–proton (pp) data taking period in 2011 and 2012 at center-of-mass energies of s=7 and 8TeV, respectively. Subsequent results from both experiments, described in Refs. [13–18], established that the measured properties of the new particle, including its spin, CP properties, and coupling strengths to SM particles, are consistent with those expected for the Higgs boson predicted by the SM. The mass of the Higgs boson has been determined to be 125.09±0.21(stat)±0.11(syst)GeV, from a combination of ATLAS and CMS measurements [19].To establish the mass generation mechanism for fermions, it is necessary to probe the direct coupling of the Higgs boson to such particles. The most promising decay channel is τ+τ−, because of the large event rate expected in the SM compared to the μ+μ− decay channel (B(H→τ+τ−)=6.3% for a mass of 125.09GeV), and of the smaller contribution from background events with respect to the bb‾ decay channel.Searches for a Higgs boson decaying to a τ lepton pair were performed at the LEP [20–23], Tevatron [24,25], and LHC colliders. Using pp collision data at s=7 and 8TeV, the CMS Collaboration showed evidence for this process with an observed (expected) significance of 3.2 (3.7) standard deviations (s.d.) [26]. The ATLAS experiment reported evidence for Higgs bosons decaying into pairs of τ leptons with an observed (expected) significance of 4.5 (3.4) s.d. for a Higgs boson mass of 125GeV [27]. The combination of the results from both experiments yields an observed (expected) significance of 5.5 (5.0) s.d. [28].This Letter reports on a measurement of the H→ττ signal strength. The analysis targets both the gluon fusion and the vector boson fusion production mechanisms. The analyzed data set corresponds to an integrated luminosity of 35.9fb−1, and was collected in 2016 in pp collisions at a center-of-mass energy of 13TeV. In the following, the symbol ℓ refers to electrons or muons, the symbol τh refers to τ leptons reconstructed in their hadronic decays, and H→τ+τ− and H→W+W− are simply denoted as H→ττ and H→WW, respectively. All possible ττ final states are studied, except for those with two muons or two electrons because of the low branching fraction and large background contribution. The analysis covers about 94% of all possible ττ final states.2

The CMS detector

The central feature of the CMS apparatus is a superconducting solenoid of 6 m internal diameter, providing a magnetic field of 3.8 T. Within the solenoid volume, there are a silicon pixel and strip tracker, a lead tungstate crystal electromagnetic calorimeter (ECAL), and a brass and scintillator hadron calorimeter (HCAL), each composed of a barrel and two endcap sections. Forward calorimeters extend the pseudorapidity coverage provided by the barrel and endcap detectors. Muons are detected in gas-ionization chambers embedded in the steel flux-return yoke outside the solenoid.Events of interest are selected using a two-tiered trigger system [29]. The first level (L1), composed of custom hardware processors, uses information from the calorimeters and muon detectors to select events at a rate of around 100 kHz within a time interval of less than 4 μs. The second level, known as the high-level trigger (HLT), consists of a farm of processors running a version of the full event reconstruction software optimized for fast processing, and reduces the event rate to about 1 kHz before data storage.Significant upgrades of the L1 trigger during the first long shutdown of the LHC have benefited this analysis, especially in the τhτh channel. These upgrades improved the τh identification at L1 by giving more flexibility to object isolation, allowing new techniques to suppress the contribution from additional pp interactions per bunch crossing, and to reconstruct the L1 τh object in a fiducial region that matches more closely that of a true hadronic τ decay. The flexibility is achieved by employing high bandwidth optical links for data communication and large field-programmable gate arrays (FPGAs) for data processing.A more detailed description of the CMS detector, together with a definition of the coordinate system used and the relevant kinematic variables, can be found in Ref. [30].3

Simulated samples

Signal and background processes are modeled with samples of simulated events. The signal samples with a Higgs boson produced through gluon fusion (ggH), vector boson fusion (VBF), or in association with a W or Z boson (WH or ZH), are generated at next-to-leading order (NLO) in perturbative quantum chromodynamics (pQCD) with the powheg 2.0 [31–35] generator. The minlo hvJ [36] extension of powheg 2.0 is used for the WH and ZH simulated samples. The set of parton distribution functions (PDFs) is NNPDF30_nlo_as_0118 [37]. The tt‾H process is negligible. The various production cross sections and branching fractions for the SM Higgs boson production, and their corresponding uncertainties are taken from Refs. [38–40] and references therein.The MG5_amc@nlo [41] generator is used for Z+jets and W+jets processes. They are simulated at leading order (LO) with the MLM jet matching and merging [42]. The MG5_amc@nlo generator is also used for diboson production simulated at next-to-LO (NLO) with the FxFx jet matching and merging [43], whereas

Image 1

2.0 and 1.0 are used for tt‾ and single top quark production, respectively. The generators are interfaced with pythia 8.212 [44] to model the parton showering and fragmentation, as well as the decay of the τ leptons. The pythia parameters affecting the description of the underlying event are set to the CUETP8M1 tune [45].Generated events are processed through a simulation of the CMS detector based on Geant4 [46], and are reconstructed with the same algorithms used for data. The simulated samples include additional pp interactions per bunch crossing, referred to as “pileup”. The effect of pileup is taken into account by generating concurrent minimum bias collision events generated with pythia. The simulated events are weighted such that the distribution of the number of additional pileup interactions, estimated from the measured instantaneous luminosity for each bunch crossing, matches that in data, with an average of approximately 27 interactions per bunch crossing.4

Event reconstruction

The reconstruction of observed and simulated events relies on the particle-flow (PF) algorithm [47], which combines the information from the CMS subdetectors to identify and reconstruct the particles emerging from pp collisions: charged hadrons, neutral hadrons, photons, muons, and electrons. Combinations of these PF objects are used to reconstruct higher-level objects such as jets, τh candidates, or missing transverse momentum. The reconstructed vertex with the largest value of summed physics-object pT2 is taken to be the primary pp interaction vertex. The physics objects are the objects constructed by a jet finding algorithm [48,49] applied to all charged tracks associated with the vertex, including tracks from lepton candidates, and the corresponding associated missing transverse momentum.Muons are identified with requirements on the quality of the track reconstruction and on the number of measurements in the tracker and the muon systems [50]. Electrons are identified with a multivariate discriminant combining several quantities describing the track quality, the shape of the energy deposits in the ECAL, and the compatibility of the measurements from the tracker and the ECAL [51]. To reject non-prompt or misidentified leptons, a relative lepton isolation is defined as:(1)Iℓ≡∑chargedpT+max⁡(0,∑neutralpT−12∑charged, PUpT)pTℓ. In this expression, ∑chargedpT is the scalar sum of the transverse momenta of the charged particles originating from the primary vertex and located in a cone of size ΔR=(Δη)2+(Δϕ)2=0.4(0.3) centered on the muon (electron) direction. The sum ∑neutralpT represents a similar quantity for neutral particles. The contribution of photons and neutral hadrons originating from pileup vertices is estimated from the scalar sum of the transverse momenta of charged hadrons in the cone originating from pileup vertices, ∑charged, PUpT. This sum is multiplied by a factor of 1/2, which corresponds approximately to the ratio of neutral to charged hadron production in the hadronization process of inelastic pp collisions, as estimated from simulation. The expression pTℓ stands for the pT of the lepton. Isolation requirements used in this analysis, based on Iℓ, are listed in Table 1

Jets are reconstructed with an anti-kT clustering algorithm implemented in the FastJet library [49,52]. It is based on the clustering of neutral and charged PF candidates within a distance parameter of 0.4. Charged PF candidates not associated with the primary vertex of the interaction are not considered when building jets. An offset correction is applied to jet energies to take into account the contribution from additional pp interactions within the same or nearby bunch crossings. The energy of a jet is calibrated based on simulation and data through correction factors [53]. In this analysis, jets are required to have pT greater than 30GeV and |η| less than 4.7, and are separated from the selected leptons by a ΔR of at least 0.5. The combined secondary vertex (CSV) algorithm is used to identify jets that are likely to originate from a b quark (“b jets”). The algorithm exploits the track-based lifetime information together with the secondary vertices associated with the jet to provide a likelihood ratio discriminator for the b jet identification. A set of pT-dependent correction factors are applied to simulated events to account for differences in the b tagging efficiency between data and simulation. The working point chosen in this analysis gives an efficiency for real b jets of about 70%, and for about 1% of light flavor or quark jets being misidentified.Hadronically decaying τ leptons are reconstructed with the hadron-plus-strips (HPS) algorithm [54,55], which is seeded with anti-kT jets. The HPS algorithm reconstructs τh candidates on the basis of the number of tracks and of the number of ECAL strips in the η–ϕ plane with energy deposits, in the 1-prong, 1-prong+π0(s), and 3-prong decay modes. A multivariate (MVA) discriminator [56], including isolation and lifetime information, is used to reduce the rate for quark- and gluon-initiated jets to be identified as τh candidates. The working point used in this analysis has an efficiency of about 60% for genuine τh, with about 1% misidentification rate for quark- and gluon-initiated jets, for a pT range typical of τh originating from a Z boson. Electrons and muons misidentified as τh candidates are suppressed using dedicated criteria based on the consistency between the measurements in the tracker, the calorimeters, and the muon detectors [54,55]. The working points of these discriminators depend on the decay channel studied. The τh energy scale in simulation is corrected per decay mode, on the basis of a measurement in Z→ττ events. The rate and the energy scale of electrons and muons misidentified as τh candidates are also corrected in simulation, on the basis of a tag-and-probe measurement [57] in Z→ℓℓ events.All particles reconstructed in the event are used to determine the missing transverse momentum, p→Tmiss. The missing transverse momentum is defined as the negative vectorial sum of the transverse momenta of all PF candidates [58]. It is adjusted for the effect of jet energy corrections. Corrections to the p→Tmiss are applied to reduce the mismodeling of the simulated Z+jets, W+jets and Higgs boson samples. The corrections are applied to the simulated events on the basis of the vectorial difference of the measured missing transverse momentum and total transverse momentum of neutrinos originating from the decay of the Z, W, or Higgs boson. Their average effect is the reduction of the pTmiss obtained from simulation by a few GeV.The visible mass of the ττ system, mvis, can be used to separate the H→ττ signal events from the large contribution of irreducible Z→ττ events. However, the neutrinos from the τ lepton decays carry a large fraction of the τ lepton energy and reduce the discriminating power of this variable. The svfit algorithm combines the p→Tmiss with the four-vectors of both τ candidates to calculate a more accurate estimate of the mass of the parent boson, denoted as mττ. The resolution of mττ is between 15 and 20% depending on the ττ final state. A detailed description of the algorithm can be found in Ref. [59]. Both variables are used in the analysis, as detailed in Section 6, and mvis is preferred over mττ when the background from Z→ℓℓ events is large.5

Event selection

Selected events are classified into the various decay channels according to the number of selected electrons, muons, and τh candidates. The resulting event samples are made mutually exclusive by discarding events that have additional loosely identified and isolated muons or electrons. Leptons must meet the minimum requirement that the distance of closest approach to the primary vertex satisfies |dz|<0.2cm along the beam direction, and |dxy|<0.045cm in the transverse plane. The two leptons assigned to the Higgs boson decay are required to have opposite-sign electric charges. In the μτh channel, events are selected with a combination of online criteria that require at least one isolated muon trigger candidate, or at least one isolated muon and one τh trigger candidate, depending on the offline muon pT. In the eτh channel, the trigger system requires at least one isolated electron object, whereas in the eμ channel, the triggers rely on the presence of both an electron and a muon, allowing lower online pT thresholds. In the τhτh channel, the trigger selects events with two loosely isolated τh objects. The selection criteria are summarized in Table 1.In the ℓτh channels, the large W+jets background is reduced by requiring the transverse mass, mT, to satisfy(2)mT≡2pTℓpTmiss[1−cos⁡(Δϕ)]<50GeV, where pTℓ is the transverse momentum of the lepton ℓ, and Δϕ is the azimuthal angle between its direction and the p→Tmiss.In the eμ channel, the tt‾ background is reduced by requiring pζ−0.85pζvis>−35 or −10GeV depending on the category, where pζ is the component of the p→Tmiss along the bisector of the transverse momenta of the two leptons and pζvis is the sum of the components of the lepton transverse momenta along the same direction [60]. This selection criterion has a high signal efficiency because the p→Tmiss is typically oriented in the same direction as the visible di-τ system in signal events. In addition, events with a b-tagged jet are discarded to further suppress the tt‾ background in the eμ channel.6

Categorization

The event sample is split into three mutually exclusive categories per decay channel. In each category the two variables that maximize the H→ττ sensitivity are chosen to build two-dimensional (2D) distributions.The three categories are defined as:

•0-jet: This category targets Higgs boson events produced via gluon fusion. The two variables chosen to extract the results are mvis and the reconstructed τh candidate decay mode (in the μτh and eτh decay channels) or the pT of the muon (in the eμ channel). The Z→ℓℓ background is large in the 1-prong and 1-prong+π0(s) τh decay modes in the μτh and eτh channels. The mvis variable is used as a final discriminant in the fit instead of mττ because it separates the signal from the Z→ℓℓ background, which peaks around the Z boson mass. The reconstructed τh candidate decay mode is used as the other discriminant in the μτh and eτh decay channels because the Z→ℓℓ background is negligible for τh reconstructed in the 3-prong decay mode, leading to an increased signal-to-background ratio for this particular decay mode, and several systematic uncertainties related to the τh decay mode can be constrained with more precision. The 2D distributions for the signal and Z→ℓℓ background in the 0-jet category of the μτh decay channel are shown in Fig. 1

(top). In the τhτh decay channel, only one observable, mττ, is considered because of the low event yields due to the relatively high pT thresholds on the τh at trigger level, and because of the sharply falling τh pT distribution. Simulations indicate that about 98% of signal events in the 0-jet category correspond to the gluon fusion production mechanism.

•VBF: This category targets Higgs boson events produced via VBF. Events are selected with at least two (exactly two) jets with pT>30GeV in the τhτh, μτh, and eτh (eμ) channels. In the μτh, eτh, and eμ channels, the two leading jets are required to have an invariant mass, mjj, larger than 300GeV. The variable pTττ, defined as the magnitude of the vectorial sum of the p→T of the visible decay products of the τ leptons and p→Tmiss, is required to be greater than 50(100)GeV in the μτh and eτh (τhτh) channels to reduce the contribution from W+jets backgrounds. This selection criterion also suppresses the background from SM events composed uniquely of jets produced through the strong interaction, referred to as quantum chromodynamics (QCD) multijet events. In addition, the pT threshold on the τh candidate is raised to 40GeV in the μτh channel, and the two leading jets in the τhτh channel should be separated in pseudorapidity by Δη>2.5. The two observables in the VBF category are mττ and mjj. The 2D distributions for the signal and Z→ττ background in the VBF category of the μτh decay channel are shown in Fig. 1 (center). Integrating over the whole mjj phase space, up to 57% of the signal events in the VBF category are produced in the VBF production mode, but this proportion increases with mjj.

•Boosted: This category contains all the events that do not enter one of the previous categories, namely events with one jet and events with several jets that fail the specific requirements of the VBF category. It contains gluon fusion events produced in association with one or more jets (78–80% of signal events), VBF events where one of the jets has escaped detection or has low mjj (11–13%), as well as Higgs bosons produced in association with a W or a Z boson decaying hadronically (4–8%). While mττ is chosen as one of the dimensions of the distributions, pTττ is taken as the second dimension to specifically target Higgs boson events produced in gluon fusion, with a Lorentz-boosted boson recoiling against jets. Most background processes, including W+jets and QCD multijet events, typically have low pTττ. The 2D distributions for the signal and W+jets background in the boosted category of the μτh decay channel are shown in Fig. 1 (bottom).

The categories and the variables used to build the 2D distributions are summarized in Table 2

. The results of the analysis are extracted with a global maximum likelihood fit based on the 2D distributions in the various signal regions, and on some control regions, detailed in Section 7, that constrain the normalizations of the main backgrounds.

Background estimation

The largest irreducible source of background is the Drell–Yan production of Z/γ⁎→ττ,ℓℓ. In order to correct the yield and distributions of the Z/γ⁎→ττ,ℓℓ simulations to better reproduce the Drell–Yan process in data, a dedicated control sample of Z/γ⁎→μμ events is collected in data with a single-muon trigger, and compared to simulation. The control sample is composed of events with two well-identified and well-isolated opposite-charge muons with pT greater than 25GeV and an invariant mass between 70 and 110GeV. More than 99% of events in this region come from Z/γ⁎→μμ decays. Differences in the distributions of mℓℓ/ττ and pT(ℓℓ/ττ) in data and in simulations are observed in this control region, and 2D weights based on these variables are derived and applied to simulated Z/γ⁎→ττ,ℓℓ events in the signal region of the analysis. In addition, corrections depending on mjj are derived from the Z/γ⁎→μμ region and applied to the Z/γ⁎→ττ,ℓℓ simulation for events with at least two jets passing the VBF category selection criteria. After this reweighting, good agreement between data in the Z/γ⁎→μμ region and simulation is found for all other variables. The simulated sample is split, on the basis of the matching between objects at the generator and at the detector levels, into events with prompt leptons (muons or electrons), hadronic decays of the τ leptons, and jets or misidentified objects at the detector level that do not have corresponding objects at generator level within ΔR<0.2. The electroweak production of Z bosons in association with two jets is also taken into account in the analysis; it contributes up to 8% of the Z boson production in the VBF category.The background from W+jets production contributes significantly to the μτh and eτh channels, when the W boson decays leptonically and a jet is misidentified as a τh candidate. The W+jets distributions are modeled using simulation, while their yields are estimated using data, as detailed below. In the boosted and VBF categories, statistical fluctuations in the distributions from simulations are reduced by relaxing the isolation of the τh and ℓ candidates, which has been checked not to bias the distributions. The simulated sample is normalized in such a way as to obtain agreement between the yields in data and the predicted backgrounds in a control region enriched in the W+jets background, which is obtained by applying all selection criteria, with the exception that mT is required to be greater than 80GeV instead of less than 50GeV. The W+jets event purity in this region varies from about 50% in the boosted category to 85% in the 0-jet category. The high-mT sidebands described above, for each category, are considered as control regions in this fit. The constraints obtained in the boosted category are extrapolated to the VBF category of the corresponding decay channel because the topology of the boosted and VBF events is similar, and few data events would pass the high-mT sideband selection in the VBF category. Fig. 2

shows the control regions with mT>80GeV in the 0-jet and boosted categories of the μτh and eτh channels. These control regions are composed of only one bin because they are used solely to constrain the normalization of the W+jets process. In the eμ and τhτh decay channels, the W+jets background is small compared to other backgrounds, and its contribution is estimated from simulations.

The QCD multijet events constitute another important source of reducible background in the ℓτh channels, and it is entirely estimated from data. Various control samples are constituted to estimate the shape and the yield of the QCD multijet background in these channels, as explained below:

1.The raw yield is extracted using a sample where the ℓ and the τh candidates have the same sign. Using this sample, the QCD multijet process is estimated from data by subtracting the contribution of the Drell–Yan, tt‾, diboson, and W+jets processes.

2.The yield obtained above is corrected to account for differences between the background composition in the same-sign and opposite-sign regions. The extrapolation factor between the same-sign and opposite-sign regions is determined by comparing the yield of the QCD multijet background for events with ℓ candidates passing inverted isolation criteria, in the same-sign and opposite-sign regions. It is constrained and measured by adding to the global fit the opposite-sign region where the ℓ candidates pass inverted isolation criteria, using the QCD multijet background estimate from the same-sign region with ℓ candidates passing inverted isolation criteria. For the same reasons as in the case of the W+jets background, the constraints are also extrapolated to the VBF signal region. Fig. 3

shows these control regions for the 0-jet and boosted categories of the μτh and eτh channels; the observable is mvis or mττ to provide discrimination between the QCD multijet and the Z→ττ processes.

3.The 2D distributions of the QCD multijet background are estimated from a region with same-sign leptons, as for the yield estimate, but the isolation of the ℓ and τh candidates is additionally relaxed to reduce the statistical fluctuations in the distributions. Again the contribution of the Drell–Yan, tt‾, diboson, and W+jets processes are subtracted from data to extract the QCD multijet contribution in this region.

The same technique is used in the eμ decay channel, but no control region is included in the fit because QCD multijet events contribute little to the total background in this decay channel.In the τhτh channel, the large QCD multijet background is estimated with a slightly different method, from a sample composed of events with opposite-sign τh satisfying a relaxed isolation requirement, disjoint from the signal region. In this region, the QCD multijet background shape and yield are obtained by subtracting the contribution of the Drell–Yan, tt‾, and W+jets processes, estimated as explained above, from the data. The QCD multijet background yield in the signal region is obtained by multiplying the yield previously obtained in the control region by an extrapolation factor. The extrapolation factor is measured in events passing identical selection criteria as those in the signal region, and in the relaxed isolation region, except that the τh candidates are required to have the same sign. The events selected with opposite-sign τh candidates passing relaxed isolation requirements form control regions, shown in Fig. 4

, and are used in the fit to extract the results.

The tt‾ production process is one of the main backgrounds in the eμ channel. The 2D distributions in all decay channels are predicted by simulation. The normalization is adjusted to the one observed in a tt‾-enriched sample orthogonal to the signal region. This control region, shown in Fig. 5

, is added to the global fit to extract the results, and is defined similarly as the eμ signal region, except that the pζ requirement is inverted and the events should contain at least one jet.

The contributions from diboson and single top quark production are estimated from simulation, as is the H→WW background.8

Systematic uncertainties

8.1

Uncertainties related to object reconstruction and identification

The overall uncertainty in the τh identification efficiency for genuine τh leptons is 5%, which has been measured with a tag-and-probe method in Z→ττ events. This number is not fully correlated among the di-τ channels because the τh candidates are required to pass different working points of the discriminators that reduce the misidentification rate of electrons and muons as τh candidates. The trigger efficiency uncertainty per τh candidate amounts to an additional 5%, which leads to a total trigger uncertainty of 10% for processes estimated from simulation in the τhτh decay channel. This uncertainty has also been measured with a tag-and-probe method in Z→ττ events.An uncertainty of 1.2% in the visible energy scale of genuine τh leptons affects both the distributions and the signal and background yields. It is uncorrelated among the 1-prong, 1-prong+π0, and 3-prong decay modes. The magnitude of the uncertainty was determined in Z→ττ events with one τ lepton decaying hadronically and the other one to a muon, by performing maximum likelihood fits for different values of the visible energy scale of genuine τh leptons. Among these events, less than half overlap with the events selected in the μτh channel of this analysis. The fit constrains the visible τh energy scale uncertainty to about 0.3% for all decay modes. The constraint mostly comes from highly populated regions with a high τh purity, namely the 0-jet and boosted categories of the μτh and τhτh channels. The decrease in the size of the uncertainty is explained by the addition of two other decay channels with τh candidates (τhτh and eτh), by the higher number of events in the MC simulations, and by the finer categorization that leads to regions with a high Z→ττ event purity. Even in the most boosted categories, reconstructed τh candidates typically have moderate pT (pT less than 100GeV) and are found in the barrel region of the detector. As tracks are well measured in the CMS detector for this range of pT, the visible energy scale of genuine τh leptons is fully correlated for all τh leptons reconstructed in the same decay mode, irrespective of their pT and η. The uncertainties in the visible energy scale for genuine τh leptons together contribute an uncertainty of 5% to the measurement of the signal strength.In the 0-jet category of the μτh and eτh channels, the relative contribution of τh in a given reconstructed decay mode is allowed to fluctuate by 3% to account for the possibility that the reconstruction and identification efficiencies are different for each decay mode. This uncertainty has been measured in a region enriched in Z→ττ events with one τ lepton decaying hadronically and the other one decaying to a muon, by comparing the level of agreement in exclusive bins of the reconstructed τh decay mode, after adjusting the inclusive normalization of the Z→ττ simulation to its best-fit value. The effect of migration between the reconstructed τh decay modes is negligible in other categories, where all decay modes are treated together.For events where muons or electrons are misidentified as τh candidates, essentially Z→μμ events in the μτh decay channel and Z→ee events in the eτh decay channel, the τh identification leads to rate uncertainties of 25 and 12%, respectively, per reconstructed τh decay mode. Using mvis and the reconstructed τh decay mode as the observables in the 0-jet category of the μτh and eτh channels helps reduce the uncertainty after the signal extraction fit: the uncertainty in the rate of muons or electrons misidentified as τh becomes of the order of 5%. The energy scale uncertainty for muons or electrons misidentified as τh candidates is 1.5 or 3%, respectively, and is uncorrelated between reconstructed τh decay modes. The fit constrains these uncertainties to about one third of their initial values. For events where quark- or gluon-initiated jets are misidentified as τh candidates, a linear uncertainty that increases by 20% per 100GeV in τh pT accounts for a potential mismodeling of the jet→τh misidentification rate as a function of the τh pT in simulations. The uncertainty has been determined from a region enriched in W+jets events, using events with a muon and a τh candidate in the final state, characterized by a large transverse mass between the pTmiss and the muon [54,55].In the decay channels with muons or electrons, the uncertainties in the muon and electron identification, isolation, and trigger efficiencies lead to the rate uncertainty of 2% for both muons and electrons. The uncertainty in the electron energy scale, which amounts to 2.5% in the endcaps and 1% in the barrel of the detector, is relevant only in the eμ decay channel, where it affects the final distributions. In all channels, the effect of the uncertainty in the muon energy scale is negligible.The uncertainties in the jet energy scale depend on the pT and η of the jet [53]. They are propagated to the computation of the number of jets, which affects the repartition of events between the 0-jet, VBF, and boosted categories, and to the computation of mjj, which is one of the observables in the VBF category.The rate uncertainty related to discarding events with a b-tagged jet in the eμ decay channel is up to 5% for the tt‾ background. The uncertainty in the mistagging rate of gluon and light-flavor jets is negligible.The p→Tmiss scale uncertainties [61], which are computed event-by-event, affect the normalization of various processes through the event selection, as well as their distributions through the propagation of these uncertainties to the di-τ mass mττ. The p→Tmiss scale uncertainties arising from unclustered energy deposits in the detector come from four independent sources related to the tracker, ECAL, HCAL, and forward calorimeters subdetectors. Additionally, p→Tmiss scale uncertainties related to the uncertainties in the jet energy scale measurement, which lead to uncertainties in the p→Tmiss calculation, are taken into account. The combination of both sources of uncertainties in the p→Tmiss scale leads to an uncertainty of about 10% in the measured signal strength.8.2

Background estimation uncertainties

The Z→ττ background yield and distribution are corrected based on the agreement between data and the background prediction in a control region enriched in the Z→μμ events, as explained in Section 7. The extrapolation uncertainty related to kinematic differences in the selections in the signal and control regions ranges between 3 and 10%, depending on the category. In addition, shape uncertainties related to the uncertainties in the applied corrections are considered; they reach 20% for some ranges of mjj in the VBF category. These uncertainties arise from the different level of agreement between data and simulation in the Z→μμ control region obtained when varying the threshold on the muon pT.The uncertainties in the W+jets event yield determined from the control regions in the μτh and eτh channels account for the statistical uncertainty of the observed data, the statistical uncertainty of the W+jets simulated sample, and the systematic uncertainties associated with background processes in these control regions. Additionally, an uncertainty in the extrapolation of the constraints from the high-mT (mT>80GeV) control regions to the low-mT (mT<50GeV) signal regions is additionally taken into account. The latter ranges from 5 to 10%, and is obtained by comparing the mT distributions of simulated and observed Z→μμ events where one of the muons is removed and the p→Tmiss adjusted accordingly, to mimic W+jets events. The reconstructed invariant mass of the parent boson in the rest frame is multiplied by the ratio of the W and Z boson masses before removing the muon. In the τhτh and eμ channels, where the W+jets background is estimated from simulation, the uncertainty in the yield of this small background is equal to 4 and 20%, respectively. The larger value for the eμ channel includes uncertainties in the misidentification rates of jets as electrons and muons, whereas the uncertainty in the misidentification rate of jets as τh candidates in the τhτh channel is accounted for by the linear uncertainty as a function of the τh pT described earlier.The uncertainty in the QCD multijet background yield in the eμ decay channel ranges from 10 to 20%, depending on the category. It corresponds to the uncertainty in the extrapolation factor from the same-sign to opposite-sign region, measured in events with anti-isolated leptons. In the μτh and eτh decay channels, uncertainties from the fit of the control regions with leptons passing relaxed isolation conditions are considered, together with an additional 20% uncertainty that accounts for the extrapolation from the relaxed-isolation control region to the isolated signal region. In the τhτh decay channel, the uncertainty in the QCD mutlijet background yield is a combination of the uncertainties obtained from fitting the dedicated control regions with τh candidates passing relaxed isolation criteria, and of extrapolation uncertainties to the signal region ranging from 3 to 15% and accounting for limited disagreement between prediction and data in signal-free regions with various loose isolation criteria.The yield of events in a tt‾-enriched region is added to the maximum likelihood fit to control the normalization of this process in the signal region, as explained in Section 7. The uncertainty from the fit in the control region is automatically propagated to the signal regions, resulting in an uncertainty of about 5% on the tt‾ cross section. Per-channel uncertainties related to the object reconstruction and identification are considered when extrapolating from the eμ final state to the others. The tt‾ simulation is corrected for differences in the top quark pT distributions observed between data and simulation, and an uncertainty in the correction is taken into account.The combined systematic uncertainty in the background yield arising from diboson and single top quark production processes is estimated to be 5% on the basis of recent CMS measurements [62,63].8.3

Signal prediction uncertainties

The rate and acceptance uncertainties for the signal processes related to the theoretical calculations are due to uncertainties in the PDFs, variations of the QCD renormalization and factorization scales, and uncertainties in the modeling of parton showers. The magnitude of the rate uncertainty depends on the production process and on the event category.The inclusive uncertainty related to the PDFs amounts to 3.2, 2.1, 1.9, and 1.6%, respectively, for the ggH, VBF, WH, and ZH production modes [38]. The corresponding uncertainty for the variation of the renormalization and factorization scales is 3.9, 0.4, 0.7, and 3.8%, respectively [38]. The acceptance uncertainties related to the particular selection criteria used in this analysis are less than 1% for the ggH and VBF productions for the PDF uncertainties. The acceptance uncertainties for the VBF production in the renormalization and factorization scale uncertainties are also less than 1%, while the corresponding uncertainties for the ggH process are treated as shape uncertainties as the uncertainty increases linearly with pTττ and mjj.The pT distribution of the Higgs boson in the powheg 2.0 simulations is tuned to match more closely the next-to-NLO (NNLO) plus next-to-next-to-leading-logarithmic (NNLL) prediction in the HRes2.1 generator [64,65]. The acceptance changes with the variation of the parton shower tune in herwig++ 2.6 samples [66] are considered as additional uncertainties, and amount to up to 7% in the boosted category. The theoretical uncertainty in the branching fraction of the Higgs boson to τ leptons is equal to 2.1% [38].The theoretical uncertainties in the signal production depend on the jet multiplicity; this effect is included by following the prescriptions in Ref. [67]. This effect needs to be taken into account because the definitions of the three categories used in the analysis are based partially on the number of reconstructed jets. Additional uncertainties for boosted Higgs bosons, related to the treatment of the top quark mass in the calculations, are considered for signal events with pTττ>150GeV.Theory uncertainties in the signal prediction contribute an uncertainty of 10% to the measurement of the signal strength.8.4

Other uncertainties

The uncertainty in the integrated luminosity amounts to 2.5% [68].Uncertainties related to the finite number of simulated events, or to the limited number of events in data control regions, are taken into account. They are considered for all bins of the distributions used to extract the results if the uncertainty is larger than 5%. They are uncorrelated across different samples, and across bins of a single distribution. Taken together, they contribute an uncertainty of about 12% to the signal strength measurement, coming essentially from the VBF category, where the background templates are less populated than in the other categories.The systematic uncertainties considered in the analysis are summarized in Table 3

Results

The extraction of the results involves a global maximum likelihood fit based on 2D distributions in all channels, shown in Figs. 6–17

, together with the control regions for the tt‾, QCD multijet, and W+jets backgrounds. The choice of the binning is driven by the statistical precision of the background and data templates, leading to wider bins in the poorly-populated VBF category. The most sensitive category, VBF, is shown first and is followed by the boosted and 0-jet categories. The signal prediction for a Higgs boson with mH=125.09GeV is normalized to its best fit cross section times branching fraction. The background distributions are adjusted to the results of the global maximum likelihood fit.

The 2D distributions of the final discriminating variables obtained for each category and each channel in the signal regions, along with the control regions, are combined in a binned likelihood involving the expected and observed numbers of events in each bin. The expected number of signal events is the one predicted for the production of a SM Higgs boson of mass mH=125.09GeV decaying into a pair of τ leptons, multiplied by a signal strength modifier μ treated as a free parameter in the fit.The systematic uncertainties are represented by nuisance parameters that are varied in the fit according to their probability density functions. A log-normal probability density function is assumed for the nuisance parameters affecting the event yields of the various background contributions, whereas systematic uncertainties that affect the shape of the distributions are represented by nuisance parameters whose variation results in a continuous perturbation of the spectrum [69] and which are assumed to have a Gaussian probability density function. Overall, the statistical uncertainty in the observed event yields is the dominant source of uncertainty for all combined results.Grouping events in the signal region by their decimal logarithm of the ratio of the signal (S) to signal-plus-background (S+B) in each bin (Fig. 18

), an excess of observed events with respect to the SM background expectation is clearly visible in the most sensitive bins of the analysis. The expected background and signal contributions, as well as the observed number of events, are indicated per process and category in Table 4

for the bins with log10⁡(S/(S+B))>−0.9. The channel that contributes the most to these bins is τhτh.

An excess of observed events relative to the background expectation is also visible in Fig. 19

, where every mass distribution for a constant range of the second dimension of the signal distributions has been summed with a weight of S/(S+B) to increase the contribution of the most sensitive distributions. In this case, S and B are computed, respectively, as the signal or background contribution in the mass distribution excluding the first and last bins, in which the amount of signal is negligible. The signal regions that use mvis instead of mττ, namely the 0-jet category of the μτh, eτh and eμ channels, are not included. The two panes of Fig. 19 group the compatible bins of Figs. 6–17.

The excess in data is quantified by calculating the corresponding local p-value using a profile likelihood ratio test statistic [70–73]. As shown in Fig. 20

, the observed significance for a SM Higgs boson with mH=125.09GeV is 4.9 standard deviations, for an expected significance of 4.7 standard deviations.

The corresponding best fit value for the signal strength μ is 1.09−0.26+0.27 at mH=125.09GeV. The uncertainty in the best fit signal strength can be decomposed into four components: theoretical uncertainties, bin-by-bin statistical uncertainties on the backgrounds, other systematic uncertainties, and the statistical uncertainty. In this format, the best fit signal strength is μ=1.09−0.15+0.15(stat)−0.15+0.16(syst)−0.08+0.10(theo)−0.12+0.13 (bin-by-bin). The individual best fit signal strengths per channel and per category, using the constraints obtained on the systematic uncertainties through the global fit, are given in Fig. 21

; they demonstrate the channel- and category-wise consistency of the observation with the SM Higgs boson hypothesis.

A likelihood scan is performed for mH=125.09GeV in the (κV,κf) parameter space, where κV and κf quantify, respectively, the ratio between the measured and the SM value for the couplings of the Higgs boson to vector bosons and fermions, with the methods described in Ref. [26]. For this scan only, Higgs boson decays to pairs of W bosons are considered as part of the signal. All nuisance parameters are profiled for each point of the scan. As shown in Fig. 22

, the observed likelihood contour is consistent with the SM expectation of κV and κf equal to unity.

The results are combined with the results of the search for H→ττ performed with the data collected with the CMS detector at center-of-mass energies of 7 and 8TeV [14], using a common signal strength for all data taking periods. All uncertainties are considered as fully uncorrelated between the different center-of-mass energies. The combination leads to an observed and an expected significance of 5.9 standard deviations. The corresponding best fit value for the signal strength μ is 0.98±0.18 at mH=125.09GeV. This constitutes the most significant direct measurement of the coupling of the Higgs boson to fermions by a single experiment.10

Summary

A measurement of the H→ττ signal strength, using events recorded in proton–proton collisions by the CMS experiment at the LHC in 2016 at a center-of-mass energy of 13TeV, has been presented. Event categories are designed to target Higgs boson signal events produced by gluon or vector boson fusion. The results are extracted via maximum likelihood fits in two-dimensional planes, and give an observed significance for Higgs boson decays to τ lepton pairs of 4.9 standard deviations, to be compared with an expected significance of 4.7 standard deviations. The combination with the corresponding measurement performed at center-of-mass energies of 7 and 8TeV with the CMS detector leads to the first observation by a single experiment of decays of the Higgs boson to pairs of τ leptons, with a significance of 5.9 standard deviations.

Acknowledgements

We congratulate our colleagues in the CERN accelerator departments for the excellent performance of the LHC and thank the technical and administrative staffs at CERN and at other CMS institutes for their contributions to the success of the CMS effort. In addition, we gratefully acknowledge the computing centers and personnel of the Worldwide LHC Computing Grid for delivering so effectively the computing infrastructure essential to our analyses. Finally, we acknowledge the enduring support for the construction and operation of the LHC and the CMS detector provided by the following funding agencies: BMWFW and FWF (Austria); FNRS and FWO (Belgium); CNPq, CAPES, FAPERJ, and FAPESP (Brazil); MES (Bulgaria); CERN; CAS, MOST, and NSFC (China); COLCIENCIAS (Colombia); MSES and CSF (Croatia); RPF (Cyprus); SENESCYT (Ecuador); MoER, ERC IUT, and ERDF (Estonia); Academy of Finland, MEC, and HIP (Finland); CEA and CNRS/IN2P3 (France); BMBF, DFG, and HGF (Germany); GSRT (Greece); OTKA and NIH (Hungary); DAE and DST (India); IPM (Iran); SFI (Ireland); INFN (Italy); MSIP and NRF (Republic of Korea); LAS (Lithuania); MOE and UM (Malaysia); BUAP, CINVESTAV, CONACYT, LNS, SEP, and UASLP-FAI (Mexico); MBIE (New Zealand); PAEC (Pakistan); MSHE and NSC (Poland); FCT (Portugal); JINR (Dubna); MON, ROSATOM, RAS, RFBR and RAEP (Russia); MESTD (Serbia); SEIDI, CPAN, PCTI and FEDER (Spain); Swiss Funding Agencies (Switzerland); MST (Taipei); ThEPCenter, IPST, STAR, and NSTDA (Thailand); TUBITAK and TAEK (Turkey); NASU and SFFR (Ukraine); STFC (United Kingdom); DOE and NSF (USA).Individuals have received support from the Marie-Curie program and the European Research Council and Horizon 2020 Grant, contract No. 675440 (European Union); the Leventis Foundation; the Alfred P. Sloan Foundation; the Alexander von Humboldt Foundation; the Belgian Federal Science Policy Office; the Fonds pour la Formation à la Recherche dans l'Industrie et dans l'Agriculture (FRIA-Belgium); the Agentschap voor Innovatie door Wetenschap en Technologie (IWT-Belgium); the Ministry of Education, Youth and Sports (MEYS) of the Czech Republic; the Council of Science and Industrial Research, India; the HOMING PLUS program of the Foundation for Polish Science, cofinanced from European Union, Regional Development Fund, the Mobility Plus program of the Ministry of Science and Higher Education, the National Science Center (Poland), contracts Harmonia 2014/14/M/ST2/00428, Opus 2014/13/B/ST2/02543, 2014/15/B/ST2/03998, and 2015/19/B/ST2/02861, Sonata-bis 2012/07/E/ST2/01406; the National Priorities Research Program by Qatar National Research Fund; the Programa Clarín-COFUND del Principado de Asturias; the Thalis and Aristeia programs cofinanced by EU-ESF and the Greek NSRF; the Rachadapisek Sompot Fund for Postdoctoral Fellowship, Chulalongkorn University and the Chulalongkorn Academic into Its 2nd Century Project Advancement Project (Thailand); and the Welch Foundation, contract C-1845.

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